\r\n\tWith a history of over 50 years since their introduction into therapy and formulation of medicinal products, hydrogels remain a challenge for researchers in the field. \r\n\tVersatile, with high-water content, tunable properties, and mild processing conditions, hydrogels advanced from simple chemically or physically crosslinked networks to complex double network composites or even more sophisticated new developments as shape memory and self-healing hydrogels. \r\n\tIncreasing knowledge in hybrid or composite hydrogel materials, controlled release of sensitive drugs, or several drugs from the same hydrogel matrix could be achieved. Parallel to targeted efforts aimed to maintain drug micro- or nanoparticle’s distinct three-dimensional structure, synergistic hybrid materials with more than one type of polymer was developed.
\r\n
\r\n\tBut one of the most challenging tasks remains further and continues to improve the clinical translation of these innovative hydrogels. That is what this book intends to provide the reader: a comprehensive overview of the current state-of-the-art, recent advances, new perspectives, and applications of the hydrogels as valuable platforms for targeted delivery. Driven by the need to ensure proper patient compliance, ease of administration, along with the possibility to modulate release and degradation profiles after administration, numerous non-topical hydrogel formulations had been reported. Smart and supramolecular hydrogels, stimuli-reactive materials, that quickly respond in mild conditions, represent today an attractive approach for minimally invasive treatments.
\r\n
\r\n\tThe book will also represent an invitation to discover “new” off-the-shelf hydrogels with highly tunable properties, with low complexity of formulation (environmentally friendly processing), but with adequate features to fulfill clinical requirements and provide desired delivery platforms for therapy.
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1. Introduction
Growth factors (GFs) have been investigated for the purpose of alveolar bone regeneration in periodontal, reconstructive and pre-prosthetic surgery, often with a view to rehabilitation with dental implants. Results are promising, and research is currently focusing on developing an effective delivery system capable of ensuring a controlled and localized GF release and activity. In fact, one of the main issues relating to GFs concerns how to control their effects over time so as to guarantee their effective action in the various phases of bone healing. This chapter provides a review of the literature on GFs used for bone regeneration in dentistry, emphasizing the most recent developments relating to local delivery systems.
2. Mechanism of action of growth factors (GFs)
Growth factors (GFs) are protein molecules that have a role in controlling biological processes, such as cell growth, proliferation, differentiation and repair. GFs cannot pass through a cell’s membrane; they must bind to high-affinity cell receptors in order to take effect. Many GFs stimulate several cell populations, while others are less versatile and specific to a particular cell line.
In dentistry, numerous GFs have been investigated in terms of their effect on hard and soft tissue healing and regeneration.
Whatever the tissue involved, the healing process always involves a series of molecular, biochemical and cellular events that can be grouped into three overlapping phases: inflammation, proliferation, and remodeling.
Inflammation begins spontaneously straight an after injury has occurred and lasts for 1 to 4 days. It is characterized by clotting in the wound, the release of signal molecules to recruit immune cells, and the release of specific enzymes (matrix metalloproteinases, MMPs) that clean the wound. The proliferative phase takes place between 4 and 21 days after wounding, when fibroblasts are stimulated to invade the site of the wound and produce extracellular matrix components. Highly-vascularized granulation tissue is formed and the gap is closed. The final remodeling phase can take up to a year, during which time the immature scar is converted into a stable, less vascularized tissue that exhibits good mechanical proprieties, followed by the growth of regenerated tissue.
GFs have been used in dentistry in all these phases. The most often studied GFs are probably the bone morphogenetic proteins (BMPs), discovered by Urist, who found that protein mixtures obtained from demineralized, lyophilized segments of bone were responsible for bone formation after implanting in rabbit muscle tissue [1].
BMPs are multifunctional cytokines that belong to the transforming growth factor-β (TGF-β) superfamily. They are not only involved in direct ectopic bone formation (hence their name of bone morphogenetic proteins), they also modulate several developmental processes, prompting numerous authors to suggest other names: for instance, Reddi suggested that they be should be called body morphogenetic proteins, given their extensive roles in various tissues [2].
Over 20 BMPs with various functions have been identified in humans. They have a major role in embryogenesis and in the maintenance and repair of many skeletal and non-skeletal tissues in adults [3]. BMP-1 is actually not considered a member of the BMP family, but a misnamed protein with chordinase and procollagen proteinase activities, implicated in pattern formation during the development of a number of organisms [4]. BMPs are mainly related to bone and cartilage formation, though BMPs 8b, 10 and 15 have no role in these processes, and BMPs 12, 13 and 14 are called cartilage-derived morphogenetic proteins (CDMPs) because they induce chondrogenic phenotypes rather than osteogenesis [2,5], whereas a definite bone-inducing role during bone formation has been observed for BMPs 2, 4, 6, 7 and 9 [6].
BMPs play a pivotal part in skeletal morphogenesis and repair, promoting the differentiation of mesenchymal cells into osteoblasts and inducing new bone formation. BMPs are involved in regulating mesenchymal cell differentiation and proliferation by stimulating intracellular signaling pathways. BMP signals are transmitted by the plasma membrane receptors to the nucleus through multiple signaling pathways that can be divided into two groups, the Smad and non-Smad pathways [3,7]. At the cell surface, BMP ligands bind with BMP receptors, triggering specific intracellular pathways that activate and influence gene transcription. Of the three types of receptor for the TGF-β superfamily, only types I and II appear to have significant roles in BMP binding and signaling. Five type I receptors (ALK1 [Acvrl1], ALK2 [ActRI], ALK3 [BRIa], ALK4 [ActRIb] and ALK6 [(BRIb]), and three type II receptors (BRII, ActRIIa, and ActRIIb) have been identified [8], plus a short form of BRII [9]. Type III TGF-β receptors have also been shown to have a role in BMP signaling, by mediating epithelial to mesenchymal cell conversion [10].
Canonical Smad-dependent TGF-β first binds to receptors type I and type II, and then signals are transduced to their Smads. Activated Smads form a complex with Smad4 and cross the nuclear membrane into the nucleus, where they regulate the expression of transcriptional factors and transcriptional coactivators that are important in osteoblasts (Dlx5, Runx2 and Osx). It has recently been demonstrated that, following TGF-β induction, the Smad and the p38 MAPK pathways converge on the Runx2 gene to control mesenchymal precursor cell differentiation [11].
As for the isolation of BMPs, after Urist’s experiments, BMPs were obtained from the bones of various species, including rabbit, cow and human. Nowadays, BMPs are produced and purified using DNA recombinant technology and essentially two expression systems, in mammalian cells or bacteria [6]. Recombinant human BMP-2 (rhBMP-2) and recombinant human BMP-7 (rhBMP-7) are currently the only proteins in the group to been approved by the US Food and Drug Administration (FDA) for clinical use in humans, which explains why they are clearly the most extensively evaluated BMPs [12].
Another GF of interest in dentistry is the growth and differentiation factor (GDF), the structure of which closely resembles some BMPs, so it could be included in the BMP family. GDF-5 is also known as BMP-14, or cartilage-derived morphogenetic protein 1, because it induces chondrogenic phenotypes rather than osteogenesis [6]. GDF-5 gene mutations give rise to different types of dysplasia and can result in the autosomal recessive syndromes of brachypod in mice and Hunter-Thompson or Grebe-type chondrodysplasia in humans, involving a loss of joints in both humans and mice [13-15]. Francis-West and colleagues [14] showed that GDF-5 can modulate the initial stages of chondrogenesis by increasing cell adhesion, and can increase chondrocyte proliferation in the later stages of skeletogenesis.
The osteoinductive potential of GDF-5 has been found smaller than that of other members of the BMP family, though numerous studies have confirmed its crucial role in skeletal morphogenesis. Several in vitro experiments have demonstrated that rhGDF-5 stimulates osteogenic differentiation and promotes angiogenic activity by increasing vascular endothelial growth factor gene expression in fat- or bone-marrow-derived stromal cells. The osteoinductive activity of rhGDF-5 has also been examined in numerous in vivo model systems [13].
Another GF extensively investigated for clinical applications is the platelet-derived growth factor (PDGF), which is synthesized by platelets, monocytes, macrophages, endothelial cells and osteoblasts. This is a dimeric molecule consisting of disulfide-bonded, structurally similar A- and B-polypeptide chains that combine to form homo- and heterodimers. The biologically most potent of these PDGFs is PDGF-BB, which has been thoroughly investigated. The PDGF isoforms exert their cellular effects by binding to and activating two structurally related protein tyrosine kinase receptors, called the alpha-receptor and the beta-receptor [16,17].
PDGF is stored in the alpha granules of circulating platelets and is released during blood clotting in the event of soft or hard tissue injury. Once it has been released from the platelets, PDGF binds to specific cell surface receptors and promotes rapid cell migration (chemotaxis) and proliferation (mitogenesis) at the site of injury. In particular, in vitro and in vivo studies have demonstrated that PDGF is a potent chemotactic and mitogenic factor for gingival and periodontal ligament fibroblasts, cementoblasts and osteoblasts [18].
Since the first animal study conducted by Lynch and co-workers [19], extensive in vitro, preclinical and clinical studies have been performed using PDGF, alone or in combination with other GFs, for incrementing bone vertically and horizontally, and for treating periodontal and peri-implant defects. The positive outcomes of these studies provide strong evidence of the safety and predictably of rhPDGF combined with specific scaffolds in periodontal and peri-implant regeneration, suggesting promising clinical applications [18,20,21].
Although a large body of preclinical and clinical data has been obtained for only a few GFs, others have nonetheless been assessed for possible applications in clinical practice.
The activity and osteoinductive potential of fibroblast growth factor (FGF) have been the object of various studies [22-24]. FGF signaling reportedly interacts with BMP signaling in bone formation, showing a synergic action on osteogenesis [11].
Few studies have considered the use of parathyroid hormone (PTH) as a factor for modulating bone augmentation and healing [25]. PTH binding activates PTH1R to stimulate several downstream effectors and also drives the internalization of the PTH1R(PTH type I receptor)-TGFβRII (TGF-β type II receptor) complex, which attenuates both TGF-β and PTH signaling on bone development. The transcriptional factor/cAMP response element binding protein (CREB) mediates PTH signaling in osteoblasts, and the PTH-CREB signaling pathway serves as an effective activator of BMP-2 expression [11].
Transforming growth factor-β (TGF-β) [26-27], vascular endothelial growth factor (VEGF) [24], and insulin-like growth factor (IGF) [28] are also the object of studies regarding the biological properties of these bioactive molecules.
3. Clinical application of GFs in dentistry
Given the biological properties of GFs, a major focus of research has concerned the clinical application of the osteoinductive proteins, such as some BMPs, for enhancing new bone formation. Bone loss involving the teeth may be secondary to diseases such as periodontitis, cystic diseases or tumors, or the consequence of trauma. Alveolar bone augmentation procedures are often needed for the purpose of inserting dental implants for prosthetic rehabilitation.
Missing teeth can be replaced with prostheses supported on dental implants, which can only be inserted in patients with an adequate alveolar ridge height and/or thickness, so bone augmentation procedures enable implant treatments in cases in which it would otherwise not be an option. Bone augmentation procedures can be performed prior to implant placement (in a two-stage procedure), or during the same surgical procedure (one-stage procedure), using numerous materials and techniques.
Various options have been described [29], including: autogenous bone grafts, allografts, xenografts, alloplastic grafts, barrier membranes for guided bone regeneration (GBR), growth factors (and BMPs in particular), platelet-rich plasma (PRP), inlay grafting, onlay grafting, ridge expansion, and distraction osteogenesis.
Tonetti et al. [30] described various techniques that have been developed to correct inadequate vertical and horizontal bone volumes, such as guided bone regeneration (GBR), sinus lift and onlay bone grafting.
Bone augmentation techniques have also been promoted as a means for treating periodontal and peri-implant diseases in an effort to regenerate lost periodontal or peri-implant soft and hard tissues [31-32].
Autogenous bone grafts are still considered the gold standard for bone repair in most cases, though there are some restrictions in their use in clinical practice because of the morbidity of the harvesting procedures and the limited amount of bone available. Many authors have consequently been studying the biocompatibility and effectiveness of other materials as potential substitutes for autogenous bone grafts.
The most recent and promising approach consists in applying osteoinductive growth factors to promote new bone formation (protein therapy) [33], providing a new alternative to autogenous grafts and other bone substitutes.
Combining growth factors with osteoinductive scaffolds may facilitate a faster and more significant enhancement of new bone formation thanks to the delivery of the growth factors at the site of the graft, and because their three-dimensional stability provides protection during the gradual replacement of the graft with newly-formed bone. Numerous materials have been used in combination with GFs, including inorganic bovine bone, porous hydroxyapatite and demineralized human bone matrix.
Numerous pre-clinical and clinical studies have looked into how GF implantation influences bone augmentation and implant osteointegration, focusing particularly on recombinant human BMP-2 (rhBMP-2), rhBMP-7 and recombinant human growth and differentiation factor-5 (rhGDF-5), combined with a variety of biomaterials used as scaffolds and delivery systems.
Although the potential value of GFs in alveolar bone regeneration and augmentation has been highlighted by numerous authors [6,31,34-35], it is still difficult to assess the different biological potential of each growth factor, because few analyses have compared different growth factors under identical in vivo conditions [24].
There is still much to learn about osteogenic growth factors: only a handful of growth and differentiation factors have been the object of clinical evaluation [6,18,25] and further studies are needed to identify predictable clinical outcomes.
3.1. Pre-prosthetic surgery for the purpose of dental rehabilitation with implants
Several surgical techniques and materials - including the use of GFs - have been introduced with a view to increasing bone volume in order to enable the placement of dental implants.
The systematic literature review conducted by Jung and coworkers [25] assessed the clinical, histological and radiographic outcomes after BMP-2, BMP-7, GDF-5, PDGF, and PTH had been used for localized alveolar ridge augmentation. Altogether, 74 studies met the authors’ inclusion criteria, including 6 on the outcome of BMP-2 for localized alveolar ridge augmentation in humans; the remainder were pre-clinical studies involving BMP-2, BMP-7, GDF-5, PDGF, and PTH. For all the GFs other than BMP-2, no human studies met the inclusion criteria. Concerning the animal studies, most of those on BMP-2 (43 out of 45) showed a positive effect of this growth factor. Six of 8 studies reported a positive effect of BMP-7. The one animal study on GDF-5 spoke of a statistically significant increase in bone volume. Five of 10 studies involving the use of PDGF also reported a statistically significant increase in bone volume. Four animal studies identified a significantly greater bone regeneration in cases treated with PTH than in controls. In the six human studies, BMP-2 influenced local bone augmentation, with a dose-dependent increase in bone volume. The dose of BMP-2 delivered seemed to have an impact on treatment outcome, local bone regeneration being greater for higher BMP-2 doses [36-38], with a smaller decrease in bone height at extraction socket sites [39]. Four of these six human studies were designed as randomized-controlled clinical trials (RCT) [37-40], the other two as prospective cohort studies [36,41]. The locally-applied dose of BMP-2 ranged from 0.5 to 1.75 mg/ml, or 0.12 to 3.4 mg/patient, respectively. An absorbable collagen sponge (ACS) was used in five studies, while Jung et al. [40] used a demineralized bovine bone matrix (DBBM) as a carrier. The treatments included sinus floor augmentation [38,41], extraction socket preservation [36-37,39], augmentation of localized ridge defects [36], and lateral ridge augmentation combined with simultaneous implant placement [40].
The 16-week open-label study conducted by Boyne and coworkers [41] assessed the safety and efficacy of implanting BMP-2 delivered on an absorbable collagen sponge (rhBMP-2/ACS) for two-stage maxillary floor sinus augmentation. The dose of rhBMP-2 ranged from 1.77 to 3.40 mg per patient. Significant bone growth was documented by computed tomographic (CT) scans in all evaluable patients (11/12), with an overall mean response of 8.51 mm in height (±4.13 mm). Histology on core bone biopsies obtained when the dental implant was inserted confirmed the good quality of the bone induced by rhBMP-2/ACS.
In a more recent RCT, Boyne and colleagues [38] found no statistically significant differences in terms of the increase in ridge height, as measured using CT scans, between their treatment and control (bone graft) groups, and even a narrower ridge width in the former after using BMP-2/ACS in two-stage maxillary floor sinus augmentations.
Bianchi et al. [37] investigated the efficacy of different concentrations of rhBMP-2 in regenerating bone in alveolar defects in the anterior maxilla, reporting a positive outcome in terms of bone volume augmentation.
Another RCT [39] compared the efficacy of rhBMP-2 in two different concentrations, delivered on ACS, with placebo ACS alone in 80 patients requiring local alveolar ridge augmentation for buccal wall defects (> or =50% buccal bone loss around the extraction socket) immediately after tooth extraction of the maxillary bicuspids. They found no statistically significant effects of BMP-2 on the treatment outcome when a lower dose was used, but a statistically significant positive effect of a higher dose (1.50 mg/ml rhBMP-2/ACS). In addition, bone density and histology revealed no differences between newly-induced and native bone.
Finally, Jung et al. [40] tested whether adding rhBMP-2 to a xenogenic bone substitute mineral could improve guided bone regeneration in the case of bone defects requiring lateral bone augmentation procedures and simultaneous implant placement. Following implant insertion (baseline), the peri-implant bone defect height was measured from the implant shoulder to the first implant-bone contact. The authors reported a positive, but statistically insignificant effect of BMP-2 on the amount of newly-formed bone (37±11.2%) compared with the control group (30± 8.9%). On the other hand, they found more mature lamellar bone (76±14.4% versus 56±18.3%) and a greater area of bone-to-graft contact (57±16.2% versus 30±22.6%) at the BMP-2-treated sites.
Various methods have been described for increasing bone volume before or at the time of positioning implants [25], one of the best-documented of these methods being GBR for intra-oral bone augmentation. To overcome some of the drawbacks of this technique, e.g. a long treatment time, the difficulty of predicting any vertical bone augmentation, the risk of infection after membrane exposure, research has concentrated on the use of bioactive molecules that induce local bone formation. Using the GBR technique, the width and height of the alveolar ridge is increased in areas of insufficient bone volume by applying barrier membranes, alone or in combination with bone grafts or substitutes.
Misch [42] published a human case series of atrophic posterior mandible augmentation prior to implant insertion, using recombinant human BMP-2 2/absorbable collagen sponge (rhBMP-2/ACS) and titanium mesh. All the 10 implants involved in the study, inserted after a 6-month healing period, became integrated and were restored with single crowns.
Many in vivo studies used critical-size supra-alveolar peri-implant defect models and other bone augmentation methods simultaneously with implant insertion. In an animal study, Sigurdsson et al. [43] found that defect sites implanted with rhBMP-2⁄ACS showed signs of a statistically significant and clinically relevant vertical alveolar bone augmentation by comparison with controls (ACS). Although the titanium implant was osseointegrated after a 16-week healing interval, the BIC (bone-to-implant contact) was lower than in resident bone, as was to be expected; the newly-induced bone was often in a thin layer on the implant surface, probably due to the unpredictability of ACS in providing adequate space for new bone formation.
Wikesjö and colleagues [44] subsequently used a critical-size supra-alveolar peri-implant defect model to study the efficacy of an ePTFE GBR device in supporting rhBMP-2⁄-induced bone formation in dogs. The space-providing macro-porous membrane was characterized by the ability to prevent the compression of the rhBMP-2/ACS construct, while allowing for vascularization via the gingival connective tissue. The authors compared GBR alone with rhBMP-2(0.4 mg)⁄ACS and rhBMP-2(0.4 mg)⁄ACS combined with GBR. Histometric analysis on block biopsies after an 8-week healing interval revealed the best results in the third sample, i.e. the GBR-rhBMP-2⁄ACS combination, which revealed bone formation filling the dome-shaped GBR device, with a vertical bone gain at the turned implants averaging 4.7 ± 0.2 mm, and an induced bone area of 9.6 ± 0.7 mm2, generating a highly-significant correlation between the induced bone area and the space provided by the GBR device. This study highlighted the crucial importance of providing space in order to obtain clinically significant benefits from a BMP construct.
Jung et al. [45] ran a randomized-controlled clinical trial with a split-mouth design, in which implants were placed in sites exhibiting lateral bone defects and patients were randomly selected for treatment with demineralized bovine bone mineral and bioresorbable collagen membrane, with (test) or without (control) the addition of rhBMP-2. After an average healing period of 6 months, a reentry operation was performed for abutment connection and prosthetic reconstruction. At the 3-year follow-up, all 34 implants in all 11 patients were clinically stable and radiologically osseointegrated. At the 5-year follow-up, 32 implants were stable and functioning, while 2 were not re-examined because the patient had moved away. The survival rate of the implants examined at 3 and 5 years was therefore 100% for both the test and the control sites. The periapical radiographs of the test and control sites also showed no peri-implant radiolucency at the 3- and 5-year follow-up examination, demonstrating healthy peri-implant tissues with minimal marginal bone loss, and only minor prosthetic complications were recorded. In short, both the test and the control sites revealed excellent clinical and radiological outcomes after 3 and 5 years, with no statistically significant differences in any of the parameters examined (though the authors emphasized the need for a larger group of patients in future studies).
In a micro-CT study in dogs, Al-Hazmi and co-workers [20] assessed the efficacy of using PDGF-BB and xenografts, with or without collagen membranes, for GBR around immediate implants with buccal dehiscence defects. They concluded that using PDGF and xenografts resulted in greater BBT (buccal bone thickness), BBV (buccal bone volume), VBH (vertical bone height) and BIC (bone-to-implant contact) when used alone rather than in combination with a collagen membrane. Their results are consistent with the report from Simion et al. [46], who said that barrier membranes may interfere with the chemotactic effect of GFs on periosteal pluripotential mesenchymal cells.
Further studies are nonetheless warranted to investigate the influence of barrier membranes on the periosteal pluripotential mesenchymal cells [20].
Most of the clinical studies on rhPDGF have focused on periodontal and peri-implant regeneration, and only a few human studies have investigated ridge preservation for implant placement in extraction socket defects [47], or three-dimensional ridge augmentation [48].
In a pilot study, Nevins et al. [47] tested whether mineralized collagen bone substitute (MCBS) combined with recombinant human platelet-derived growth factor-BB (0.3 mg/mL) could generate enough viable bone in buccal wall extraction defects to enable implant placement.
In a more recent clinical study, Nevins and colleagues [49] focused on human buccal plate extraction socket regeneration with recombinant human platelet-derived growth factor BB or enamel matrix derivative. Buccal plate resorption is a critical issue when it comes to implant placement. They compared four groups: A (mineral collagen bone substitute [MCBS] scaffold alone), B (MCBS with recombinant human platelet-derived growth factor BB [rhPDGF-BB; 0.3 mg/mL]), C (MCBS with enamel matrix derivative [EMD]), and D (a combination of EMD with bone ceramic). Grafting was done at the time of extraction, advancing the buccal flap for primary closure. Histology on trephine core biopsies of the implant site performed 5 months later, at the time of implant placement, identified new bone healing around the biomaterial scaffolds with no statistically significant differences between the four treatment groups. There was a histomorphometric trend towards a greater quantity of new bone in the rhPDGF-BB-treated group, with the most favorable ridge morphology for the purposes of an optimal implant placement at reentry surgery.
Simion et al. [48] reported on two human cases of patients who underwent three-dimensional ridge augmentation using a xenograft combined with rhPDGF-BB. In the first patient, a deproteinized bovine block infused with rh-PDGF was attached to the alveolar crest with two screws to obtain a horizontal ridge augmentation. The second patient underwent a vertical ridge augmentation procedure involving deproteinized bovine bone particles embedded in a collagen matrix soaked in rhPDGF-BB. Three titanium dental implants were placed in each patient 5 months later with excellent clinical and histological outcomes, mean that rhPDGF-BB in combination with a deproteinized bovine graft has promise in applications for regenerating large three-dimensional alveolar defects in humans.
3.2. Dental implant surface coatings with GFs
Another interesting approach to enhancing alveolar ridge augmentation with a view to dental implant placement involves using implants coated with GFs.
Wikesjo and colleagues [35] reviewed the literature on implants coated with a bone-inductive factor capable of stimulating local bone formation and osseointegration. They concluded that rhBMP-2 can be delivered successfully for the purposes of inducing local bone formation and osseointegration by using screw-type endosseous oral implants with titanium oxide surfaces with open pores as a carrier. They also found that purpose-designed implant surfaces coated with rhBMP-2 resulted in the formation of Type II bone and significant osseointegration without any need for biomaterials or devices for GBR.
In an in vivo animal model, Susin et al. [50] used the critical-size supra-alveolar peri-implant defect model to assess the potential of a purpose-designed porous titanium oxide implant surface coated with rhBMP-7 for inducing alveolar bone formation and enhancing osseointegration. The animals received implants coated with rhBMP-7 at 1.5 or 3.0 mg/ml randomized to the contralateral jaw quadrants. The authors found clinically relevant bone formation and osseointegration with no statistically significant differences in terms of bone formation between the sites treated with rhBMP-7 at 1.5 or 3.0 mg/ml. Histology showed an increase in the height and area of the bone, and the newly-formed bone exhibited the same characteristics as the contiguous resident bone. Their observations support the significant clinical value of rhBMP-7 in inducing bone regeneration, but the authors made the point that higher concentrations were associated with some local side effects.
Other authors [e.g. 51-52] have investigated in vivo the potential of an rhGDF-5 coating on an oral implant with a porous titanium oxide surface for stimulating local bone formation, including osseointegration and vertical augmentation of the alveolar ridge.
Polimeni and co-workers [51] examined a bilateral critical-size, 5 mm, supra-alveolar peri-implant defect model in dogs. Six animals received implants coated with 30 or 60 µg rhGDF-5, and another six animals received implants coated with 120 µg rhGDF-5 or left uncoated (controls). The implants coated with rhGDF-5 displayed only limited peri-implant bone remodeling in the resident bone, as measured using fluorescent bone markers, with the 120 µg dose coinciding with a more advanced remodeling than the 60 and 30 µg doses. These results suggest a dose-dependent osteoinductive and/or osteoconductive effect of rhGDF-5-coated oral implants. Leknes et al. [52] performed an in vivo study in dogs that consisted in placing different kinds of implant in the alveolar ridge of the posterior mandible following the surgical extraction of the premolars and reduction of the alveolar ridge. Six animals were treated with implants coated with rhGDF-5 in doses of 30 or 60 μg/implant in contralateral jaw quadrants, while six received implants coated with rhGDF-5 at 120 μg/implant or uncoated implants (for control purposes), using a split-mouth design. The radiographs showed a dose-dependent formation of mineralized tissue significantly greater than around the uncoated implants, the greatest increase corresponding to the implants coated with 60 μg and 120 μg of rhGDF-5, and amounting to approximately 2.2 mm in both cases at 8 weeks. The authors also reported no adverse events, such as peri-implant bone remodeling, implant displacement, or seroma formation.
The above-mentioned studies indicate that these GFs have great potential for stimulating clinically relevant local bone formation, though it should be emphasized that further studies are essential to address their most appropriate dosage, carriers, and applications, as well as the long-term prognosis of GF-coated titanium implants.
3.3. Maxillary sinus lift procedure
Sinus floor elevation with immediate or delayed dental implant placement is a well-known technique for dental rehabilitation in cases of severe atrophy of the posterior maxilla due to the extension and pneumatization of the maxillary sinus. Many materials, such as autografts, xenografts, and synthetic bone substitutes, have been shown to achieve acceptable clinical results when used in maxillary sinus floor augmentations [53]. The use of GFs with various carriers and dosages has recently been investigated in combination with sinus augmentation procedures too.
Ho and colleagues [54] assessed the efficacy of various bioimplants used in maxillary sinus lift procedures with the lateral window approach in a rabbit model. They compared particulated autogenous bone, demineralized bone matrix (DBM), DBM combined with purified BMP-7 (BMP-7/DBM bioimplants), and bioimplants consisting of a poloxamer gel with BMP-7 in two different doses. In their animal model, BMP-containing bioimplants had produced more new bone and a greater new bone surface area at 2 weeks than autografts, but the advantage of these bioimplants subsequently seemed to be lost, since the differences between the bioimplants and the autografts had disappeared by 8 weeks. The authors concluded that BMP-containing bioimplants prompt a more rapid bone formation, possibly offering a greater implant stability earlier in the healing period, and therefore enabling clinicians to place osseointegrated implants in augmented maxillae sooner after grafting.
In a clinical study, Boyne and colleagues [38] compared different concentrations of rhBMP-2 (0.75 and 1.5 mg/mL), delivered on an absorbable collagen sponge (ACS) carrier, with bone grafts to identify a safe and effective concentration of rhBMP-2 for use in maxillary sinus floor augmentation procedures. Judging from density measurements on CT scans obtained before and 4 months after treatment, and 6 months after functional loading of the dental implants, and from core biopsies obtained at the time of placing the dental implant, they established that the 1.5 mg/mL dose of rhBMP-2/ACS was more appropriate in a pivotal, randomized, multicenter study to compare rhBMP-2/ACS with conventional bone graft for staged maxillary sinus floor augmentation to support dental implants for long-term functional loading.
These data prompted a randomized, parallel evaluation of rhBMP-2/ACS and autogenous bone grafts for two-stage maxillary sinus floor procedures [55]: 160 individuals with less than 6 mm of native bone height in the posterior maxilla were randomized for treatment with 1.5 mg/mL rhBMP-2/ACS or an autograft. Height and density measurements were obtained on CT scans, and core biopsies obtained at the time of dental implant placement underwent histological examination. A significant amount of new bone had formed by 6 months postoperatively in both treatment groups, but there was a significant difference in the density of the newly-induced bone at the 6-month follow-up, which was denser in the bone graft group than in the group treated with rhBMP-2/ACS. Six months after dental restoration (functional loading), however, the bone induced in the rhBMP-2/ACS group was significantly denser than in the bone graft group. No major differences emerged between the two groups in terms of the histological parameters. 17% of the patients in the autograft group experienced long-term parasthesia, pain, or gait disturbance relating to the bone graft harvest. Adverse reactions frequently recorded in the rhBMP-2/ACS group related to excessive facial swelling, and this edema was attributed to the chemotactic cellular recruitment to the site of rhBMP-2 implantation and neovascularization of the grafted area; although it was severe, this edema did not adversely affect the outcome. This study confirmed the efficacy and safety of rhBMP-2/ACS by comparison with bone grafting for sinus floor augmentation, given the morbidity, cost, and increased surgical time associated with the harvesting of autogenous bone.
Kao and coworkers [56] measured the bone formation after a lateral window sinus augmentation with recombinant human BMP-2/ absorbable collagen sponge (rhBMP-2/ACS) in combination with Bio-Oss by comparison with the results achieved with a Bio-Oss graft alone. Histology demonstrated that less new bone formed in patients treated with rhBMP-2/ACS + Bio-Oss than in those treated with Bio-Oss alone, pointing to a negative effect on bone formation of combining rhBMP-2 with Bio-Oss for maxillary sinus augmentation.
Gruber and coworkers [57] studied a GF closely related to the BMP family - the recombinant human growth and differentiation factor-5 (rhGDF-5) - in an in vivo study involving the use of different materials in sinus floor augmentation procedures in Goettingen miniature pigs. They demonstrated that associating rhGDF-5 with β-tricalcium phosphate (β-TCP) enhanced bone formation by comparison with the results obtained using the β-TCP carrier material alone.
In a further study using a split-mouth study design, the same authors [13] compared rhGDF-5-coated β-TCP with particulated autogenous bone grafts combined with the scaffold material (β-TCP). In each minipig, the sinus floors were augmented (simultaneously inserting the dental implants) with β-TCP mixed with autogenous cortical bone chips on one side, and using β-TCP coated with two different concentrations of rhGDF-5 on the contralateral side. Histology and histomorphometric analyses demonstrated that rhGDF-5-coated β-TCP not only enhanced new bone formation, but also - by comparison with a combination of β-TCP and autogenous bone chips - induced a significant increase in VD (volume density) and BIC (bone-to-implant contact) in the augmentation material.
Stavropoulos et al. [58] ran a prospective, multicenter, randomized clinical trial to examine the histological outcome of maxillary sinus lifting with rhGDF-5/β-TCP or β-TCP and autogenous bone (β-TCP/AB) composite. Thirty-one patients requiring unilateral maxillary sinus floor augmentation with a residual alveolar bone height <5 mm were treated using a lateral window approach. Cylindrical biopsies were harvested with a trephine bur during implant site preparation 3 or 4 months after sinus floor augmentation (three groups (a) rhGDF-5/b-TCP and a 3-month healing period, (b) rhGDF-5/b-TCP and a 4- month healing period, and (c) b-TCP/AB and a 4-month healing period). Histological and histometric analyses showed that sinus augmentation with rhGDF-5/β-TCP resulted in new bone in comparable amounts and of similar quality to the bone obtained with a β-TCP/AB composite graft, suggesting that rhGDF-5/β-TCP could eliminate the need for AB grafting in sinus lift procedures.
Though these favorable regenerative findings are encouraging, further studies are needed to ascertain the influence of GFs on the amount and quality of new bone formation, and on the implant survival rate after sinus lift procedures.
3.4. Periodontal regeneration
Periodontitis is a widely prevalent inflammatory disease of the tissues supporting the teeth, characterized by a progressive loss of bone and attachment.
The ultimate goal of periodontal therapy is the regeneration of periodontal tissues, which consists in stimulating new cementum formation, new alveolar bone apposition, and a functionally-oriented periodontal ligament reconstruction. Various techniques have been suggested for promoting periodontal tissue regeneration, using different bone graft materials that have gained clinical acceptance in the treatment of periodontal defects.
To overcome the weaknesses of conventional regenerative procedures, the predictability of which may be limited to selected case types, using GFs with biocompatible scaffolds to promote tissue regeneration may represent a new and promising periodontological approach.
After preliminary in vitro experiments, extensive in vivo preclinical studies have been performed to assess the potential and safety of using various GFs, alone or in combination, to treat periodontal defects.
A recent animal study by Oortgiesen et al. [23] investigated the regenerative potential of an injectable macroporous calcium phosphate cement (CaP) combined with BMP-2 or fibroblast growth factor-2 (FGF-2) in intrabony defects. After 12 weeks, only the CaP revealed limited effects on both periodontal ligament (PDL) and bone healing, while a good response in terms of bone healing was also seen with CaP/BMP-2 and CaP/FGF-2. The best PDL healing scores coincided with the combined CaP/FGF-2 treatment, suggesting that associating a topical application of FGF-2 with an injectable CaP might be a promising treatment for the purposes of periodontal regeneration.
Ishii and colleagues [22] investigated the effect of the combined use of basic FGF-2 and beta tricalcium phosphate (β-TCP) on root coverage in a dog model, finding that FGF-2/β-TCP enhanced the formation of new bone and cementum without any significant root resorption.
Kitamura et al. [59] undertook a multi-center, randomized, double-blind, placebo-controlled, dose-finding study on the potential of local applications of FGF-2 in periodontal regeneration. Modified Widman periodontal surgery was performed, during which 200 μL of the investigational formulation containing 0% (vehicle alone), 0.2%, 0.3%, or 0.4% FGF-2 was administered to 2- or 3-walled vertical bone defects in 253 adult patients with periodontitis. The primary outcome was the percentage of bone fill visible on radiographs 36 weeks after administering the treatment. All the doses of FGF-2 were significantly superior to the vehicle alone (p < 0.01) in terms of the percentage of bone fill, and this percentage peaked in the 0.3% FGF-2 group. No significant differences were observed between the four groups in terms of the regained clinical attachment (CAL), with all patients scoring around 2 mm (this was judged to be due to the different healing patterns between the FGF-2 groups and the ‘vehicle alone’ group). Conventional periodontal surgery (which corresponds to the ‘vehicle alone’ group) usually gives rise to long junctional epithelial attachments, but manual probing cannot precisely distinguish fibrous from epithelial attachments, so the difference in healing pattern cannot be reflected in the CAL regained by the different treatment groups. This limitation could have been overcome by histology, but this was not done for ethical reasons. No clinical safety issues emerged in this study. These results support the efficacy and safety of topical FGF-2 applications for periodontal regeneration in humans.
When implanted in furcation defects exposed surgically or by inflammatory processes in Papio ursinus, recombinant human osteogenic protein-1 (hOP-1) or BMP-7 tends to induce cementogenesis with the insertion of de novo generated Sharpey’s fibers. Long-term studies on P. ursinus after hOP-1 implantation show a highly-organized periodontal ligament space with periodontal ligament fibers cursing from the newly-formed and mineralized cementum to the regenerated alveolar bone, with a multitude of supporting capillaries throughout the periodontal ligament space [60].
In an experimental study by Teare et al. [27], binary applications of hOP-1 and hTGF-β(3) were implanted in Class II furcation defects of the mandibular molars of Chacma baboons (P. ursinus) to induce periodontal tissue regeneration. Sixty days after implantation, the animals were killed and histological and histomorphometric studies led the authors to conclude that hOP-1 and hTGF-β(3) in Matrigel(®) matrix induced substantial periodontal tissue regeneration and cementogenesis.
In their review, Ripamonti et al. [61] emphasized the induction of bone formation by the osteogenic proteins of the TGF-beta superfamily in the nonhuman primate, P. ursinus.
In a recent study in beagle dogs, Kim and co-workers [62] compared a candidate β-tricalcium phosphate (β-TCP) carrier technology with the absorbable collagen sponge (ACS) benchmark for supporting rhGDF-5-stimulated periodontal wound healing/regeneration in intrabony periodontal defects. Both solutions stimulated the formation of functionally-oriented periodontal ligament, cellular mixed-fiber cementum, and woven/lamellar bone, but bone regeneration (height and area) was significantly greater for the rhGDF-5/β-TCP construct. The structural integrity of the β-TCP carrier preventing compression while providing a framework for bone ingrowth may account for these results.
A phase IIa randomized controlled clinical and histological pilot study was conducted to assess rhGDF-5/β-TCP for periodontal regeneration [63]. Twenty chronic periodontitis patients participated in the study, each with at least one tooth scheduled for extraction with a probing depth (PD) ≥6 mm and an associated intrabony defect ≥4 mm following basic periodontal therapy. Participants (one defect/patient) were randomized to receive open flap debridement (OFD) + rhGDF-5/β-TCP (n = 10) or OFD alone (control; n = 10). Both protocols resulted in statistically significant clinical improvements. Descriptive statistics showed a greater reduction in PD after OFD with rhGDF-5/β-TCP than after OFD alone (3.7 ± 1.2 versus 3.1 ± 1.8 mm; p = 0.26), as well as less gingival recession (0.5 ± 0.8 versus 1.4 ± 1.0 mm; p < 0.05) and a greater CAL gain (3.2 ± 1.7 versus 1.7 ± 2.2 mm; p = 0.14) at the deepest aspect of the defect. Block biopsies of the defect sites were collected 6 months after surgery and prepared for histology. Five biopsies (1 rhGDF-5/β-TCP; 4 OFD) were deemed unsuitable for histological or histometric evaluation. Bone regeneration height (2.19 ± 1.59 versus 0.81 ± 1.02 mm; p = 0.08) and PDL (2.16 ± 1.43 versus 1.23 ± 1.07 mm; p = 0.26), cementum (2.16 ± 1.43 versus 1.23 ± 1.07 mm; p = 0.26) and bone regeneration area (0.74 ± 0.69 versus 0.32 ± 0.47 mm2; p = 0.14) were greater at sites treated with rhGDF-5/β-TCP compared to controls. These differences failed to reach statistical significance, however, and the authors said that further studies on larger samples will be needed to verify these findings.
The potential of PDGFs for promoting new bone formation and/or periodontal wound healing/regeneration has been examined in a variety of pre-clinical animal models. In vivo experimental studies have been performed using PDGF-BB alone or in combination with other GFs, such as insulin-like growth factor (IGF), and shown that these growth factors promoted new bone, cementum and periodontal ligament formation in vivo.
The first human clinical trial testing the effect of rhPDGF/rhIGF-I in periodontal defects was reported by Howell and colleagues [64] with promising results.
Early human clinical studies used rhPDGF-BB combined with bone allografts. An alternative is to use a synthetic system, such as β-tricalcium phosphate (β-TCP). Since rhPDGF applications have proved clinically effective in the treatment of intrabony defects, this growth factor has also been considered for the treatment of soft tissue recession defects [18].
Jayakumar and coworkers [65] ran a double-blind, prospective, parallel, active-controlled, randomized, multi-center clinical trial on the efficacy and safety of rhPDGF-BB with β-TCP in human intraosseous periodontal defects. Fifty-four patients with periodontal osseous defects were randomly grouped for treatment with rhPDGF-BB/β-TCP or β-TCP alone. A total number of 50 defects in 25 patients in the rhPDGF-BB/β-TCP group and 25 in the β-TCP group were ultimately available for statistical analysis. The radiographic parameters considered were linear bone growth (LBG) 6 months after surgery and percent bone fill (% BF), both of which were found significantly higher in the rhPDGF-BB/β-TCP group than in the β-TCP group. There also emerged a significantly higher area under the curve for clinical attachment level gain from 0 to 6 months, and a greater reduction in PD at the third and sixth month than after β-TCP treatment alone. The implantation of rhPDGF-BB/β-TCP for the treatment of intraosseous periodontal defects was safe and well tolerated, and resulted in clinically and statistically significant improvements in bone formation parameters and soft tissue outcomes.
Preliminary investigations thus indicate that GFs have great potential for improving periodontal regeneration, but randomized clinical trials must be conducted to gain a better understanding of the role of GFs in periodontal treatments, focusing particularly on establishing the safety and efficacy of their application.
4. Growth factor delivery systems
The great potential of GFs in bone regeneration has been discussed by numerous authors [6,31,34-35]. BMP-2 and BMP-7 have a marked effect on bone and cartilage growth and the maintenance of homeostasis during bone remodeling [66]. One of their limitations, on the other hand, seems to be the unpredictable nature of the resulting tissue regeneration in vivo. It has been suggested that the clinical efficacy of recombinant human forms of BMPs (rh-BMPs) depends on the carrier system used to ensure an effective delivery of adequate protein concentrations to the site being treated [67]. BMPs are soluble proteins and, delivered in a buffer solution, they undergo rapid degradation, leading to an insufficient bioavailability. Other factors, such as protein competition, enzymatic activity, temperature, pH and salt concentration, may also influence the total amount of active protein available immediately after its administration [68].
In 2007 Giannoudis et al. [69] came up with the “Diamond Concept” to describe the conditions needed for osteogeneration, i.e. mechanical stability at the site of the defect, and osteogenic cells combined with osteoinductive growth factors and a suitable carrier or delivery system.
The main purpose of the delivery system is to ensure adequate protein concentrations at the defect site for as long as it takes to enable the regenerative cells to migrate, proliferate and differentiate [33].
A localized, controlled release is also necessary to prevent any unwanted and uncontrolled ectopic bone formation in non-bony body tissues [70]. Supra-physiological concentrations resulting from imperfect GF release kinetics have been correlated with severe clinical complications, including generalized hematomas in soft tissues and peri-implant bone resorption. Other potential concerns theoretically include carcinogenicity and teratogenic effects [70].
Few authors have investigated the influence of GF release kinetics on bone regeneration. In physiological bone repair, some growth factors (such as BMP-2) are expressed mainly during the early inflammatory phase. Others are up-regulated during the chondrogenic and osteogenic phases, and have a biphasic expression pattern or are constitutively expressed [33]
In vivo studies demonstrated that higher BMP-2 retention times were more osteoconductive [71], and that prolonged BMP-2 delivery enhanced the protein’s osteogenic efficacy by comparison with a shorter-term delivery of an equivalent dose in a rat model [72]. Release should preferably be sustained over time, either in large single doses or in multiple smaller-dose applications. In evaluating the timing of the protein release, it is important to consider the dynamic nature of the healing zone, which depends on the type, location and appearance of the defect, the patients’ age and gender, their hormone and nutritional state, and any diseases, as well as other parameters influencing release rate, including the protein’s size and conformational changes, solubility, polymer/scaffold composition/geometry, and molecular weight [33].
Dose and concentration parameters are available for orthopedic clinical applications, where different anatomical sites require different therapeutic doses depending on the degree of vascularization, defect size and the number of resident responding cells. Supraphysiological dosages range from 0.01 mg/ml in small animal models (e.g. rats) to 0.4 mg/ml in rabbits, to more than 1.5 mg/ml in non-human primates [33].
Growth factor release from a delivery system may be diffusion-controlled, chemical or enzymatic reaction-controlled, solvent-controlled, or controlled by a combination of these mechanisms. Diffusion-controlled release is governed by the protein’s solubility and diffusion coefficient in the aqueous medium, protein partitioning between the aqueous medium and the material of the delivery system, protein loading and the diffusional distance. Chemical or enzymatic reaction-controlled systems include erodible systems, in which the protein is physically immobilized in the carrier matrix and released as the carrier undergoes degradation and dissolves. In solvent-controlled systems, the protein is embedded in a carrier matrix and a diffusional release occurs as a consequence of the rate-controlled penetration of the solvent (water) in the system [33].
Several GF delivery systems and carriers have been suggested for use in bone regeneration applications in an effort to find the optimal strategy for optimizing their clinical effectiveness and minimizing complications.
Delivery systems and carriers used for bone GFs should meet general requirements (Table 1) such as biocompatibility, predictable biodegradability, and the ability to provoke appropriate inflammatory responses. They must also have the following features: easy and cost-effective to manufacture; stability; easy handling and storage [33].
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Biocompatibility
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Predictable biodegradability
\n\t\t
\n\t\t
\n\t\t\t
Low immunogenicity and antigenicity
\n\t\t
\n\t\t
\n\t\t\t
Enhancement of cellular vascularization and attachment
\n\t\t
\n\t\t
\n\t\t\t
Affinity with BMPs and bone
\n\t\t
\n\t\t
\n\t\t\t
Maintenance and enhancement of BMP bioactivity
\n\t\t
\n\t\t
\n\t\t\t
Malleability and ease of manufacture
\n\t\t
\n\t\t
\n\t\t\t
Safety, stability, sterility, availability and cost-effectiveness
\n\t\t
\n\t\t
\n\t\t\t
Regulatory agency approval for the clinical application of interest
\n\t\t
\n\t\t
\n\t\t\t
Controlled protein release at an effective dose for the appropriate period of time
\n\t\t
\n\t
Table 1.
General requirements for BMP delivery systems
Carrier materials have been generally divided into four classes (Table 2): natural-origin polymers (collagen, hyaluronic acid, gelatin hydrogel complex, alginates and chitosan); inorganic materials (synthetic bone grafts, hydroxyapatite, calcium phosphates and bioactive glasses); synthetic biodegradable polymers (polylactic acid PLA, polyglycolide PLG, and their polymers PLGA, cholesterol-bearing pullulan nanogel CHPA), and composites (combinations of materials from the above different classes) [33].
To date, only BMP-2 and BMP-7 have been approved by the US Food and Drug Administration for human use in specific orthopedic applications, delivered using absorbable collagen sponges [33].
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
Class
\n\t\t\t
Types
\n\t\t\t
Advantages
\n\t\t\t
Disadvantages
\n\t\t
\n\t\t
\n\t\t\t
Natural polymers
\n\t\t\t
Collagen (gels, nano fibers, scaffolds and films) Fibrin glue Alginate and chitosan
\n\t\t\t
Biocompatible, biodegradable, soluble in physiological fluids, natural affinity with BMPs
\n\t\t\t
Immunogenicity (xenogenic), pathogen transmission, sensitivity to sterilization process
\n\t\t
\n\t\t
\n\t\t\t
Inorganic materials
\n\t\t\t
Synthetic bone grafts CPC (calcium phosphate cement) Bioactive glasses, hydroxyapatite, hyaluronic acid, tricalcium phosphates, metal, ceramics and calcium sulfate
\n\t\t\t
Osteoconductive, affinity with BMPs
\n\t\t\t
Brittle, difficult mold, some formulations are exothermic
\n\t\t
\n\t\t
\n\t\t\t
Synthetic polymers
\n\t\t\t
PLLA and PGLA and their copolymers CHPA
\n\t\t\t
Easy to process and sterilize, flexible to tailor and reproducible, excellent chemical and mechanical properties
\n\t\t\t
Inflammatory response, localized pH drop and limited biological function
\n\t\t
\n\t\t
\n\t\t\t
Composites
\n\t\t\t
Collagen-HA and titanium PLLA
\n\t\t\t
Depending on the combination of the different materials’ characteristics
\n\t\t\t
Complex to manufacture
\n\t\t
\n\t
Table 2.
Major classes of carrier materials
4.1. Collagen
Collagen is the protein most abundant in the connective tissue of mammals and the main non-mineral component of bone. It has been prepared in powders, membranes, films and implantable absorbable sponges, as well as in aqueous forms. Although it is versatile and easy to manipulate, the manufacture of collagen carriers is highly sensitive to several factors (including mass, soaking time, protein concentration, sterilization, buffer composition, pH and ionic strength) that directly affect rhBMPs binding [73]. Absorbable collagen sponges (ACS) have been evaluated in numerous in vivo models and clinical trials [6, 38,74-76]. In patients requiring staged maxillary sinus floor augmentation, rhBMP-2/ACS safely induced adequate bone formation for the purpose of placing and functionally loading endosseous dental implants [38]. The use of rhBMP-2/ACS without any concomitant bone grafting materials in critical-size mandibular defects prompted an excellent regeneration in a case review of 14 patients [75]. On the other hand, a recent study by Kao et al. demonstrated a more limited bone formation after a lateral-window sinus augmentation procedure involving rhBMP-2/ACS combined with Bio-Oss than when Bio-Oss was used alone [56].
Although they do away with the need to harvest autologous bone (with the associated pain), the use of animal-derived collagens is limited by their xenogenic nature: anti-type I collagen antibodies reportedly developed in almost 20% of patients treated with rhBMP-2/ACS [6]. In addition, collagen sponges are usually sterilized with ethylene oxide prior to soaking the sponge in the BMP solution, and this can affect the GF release kinetics or the protein’s bioactivity [73].
4.2. Alginate and chitosan
Alginate is a non-immunogenic polysaccharide used in a wide range of tissue engineering applications for its gel-forming properties. Alginate hydrogels allowing for a controlled, prolonged release of BMPs have only been studied in the preclinical phase, with promising results in vitro [72,77]
Chitosan is a cationic glucopolymer well known for its biological, chelating and adsorbing properties, and has been used as a BMP-2 carrier in a rat critical-size mandibular defect model, with positive results on histological and histomorphometric analysis [78].
4.3. Hyaluronic acid
Hyaluronic acid is a naturally-occurring biopolymer that plays a significant part in wound healing. It has been associated with an improved bone formation in mandibular defects by comparison with collagen sponges, when both were used to carry rhBMP-2 [79].
4.4. Hydroxyapatite
Hydroxyapatite (HAP) is well known for its osteoconductivity and has been widely used as a bone substitute material in clinical practice since the 1970s because of its ability to bond directly with bone [80]. Synthetic HAP comes in ceramic or non-ceramic, cementable forms, and has been evaluated as a scaffold and a controlled-release carrier, demonstrating lack of resorption and limited bone induction [6]. It has been combined with tri-calcium phosphates, collagen and other materials to form rigid, resorbable, porous carriers, in which case delivery and bone formation were generally found better than when HAP was used alone [81,82].
4.5. Synthetic biodegradable polymers
Unlike natural polymers and collagen, synthetic polymers pose no problem of immunogenicity or risk of disease transmission.
The most commonly-used polymers are polylactic acid (PLLA) and polyglycolic acid (PLGA). Bioresorbable PLLA/PLGA copolymers have been found superior to collagen when used to deliver rh BMP-2 to mandibular defects in the rat [83].
4.6. Bone grafts and derived composite materials
Bone grafts act as scaffolds for the ingrowth of vessels and bone-forming cells. During this osteoconductive bone regeneration process, the scaffold allows for bone to grow on its surface and inside the pores in the material. Given the biological limitations of other osteoconductive materials and the donor site morbidity after bone harvesting, the combination of osteoconductive scaffolds with osteoinductive proteins, such as BMPs, has been a major focus of research. [13,84]
Bone substitutes for use in dental and maxillofacial surgery are classified in three groups according to their origin. Allogenic bone grafts are derived from human donors, xenogenic bone grafts from other species (mostly bovine, but also equine, porcine and coralline), and the last group comprises the synthetically-produced materials. Synthetic bone grafts aim to imitate the natural bone’s structure. The most widely used are the calcium phosphates, including hydroxyapatite, tri-calcium phosphates (TCP) and composites of the two. By means of a thermal treatment (sintering) and subsequent cooling they can be transferred into ceramics with a very solid but porous structure and a rough surface closely resembling human bone.
Recent studies have reported successful bone regeneration after grafting on periodontal defects, using sinus floor elevation techniques, and in post-extraction socket defects using TCP carriers [58,65, 85].
Clinical studies reporting results of GFs delivery systems in oral surgery are revised in Table 3.
Some authors have also investigated the application of GFs to dental implant surfaces to stimulate local bone formation and osteointegration. In preclinical studies, functionalized titanium implant surfaces coated with rhBMP-2 have been shown to be able to stimulate bone formation around implants [35, 86]
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
References
\n\t\t\t
Study design
\n\t\t\t
Total number of patients
\n\t\t\t
Protein
\n\t\t\t
Carrier
\n\t\t\t
Application
\n\t\t\t
Main findings
\n\t\t
\n\t\t
\n\t\t\t
Jung et al. 2003 [40]
\n\t\t\t
RCT
\n\t\t\t
11
\n\t\t\t
rhBMP-2
\n\t\t\t
Xenogenic bone (Bio-Oss)
\n\t\t\t
Maxillary implant placement
\n\t\t\t
rhBMP-2 has the potential to predictably improve and accelerate guided bone regeneration therapy
\n\t\t
\n\t\t
\n\t\t\t
Boyne et al. 2005 [38]
\n\t\t\t
RCT
\n\t\t\t
48
\n\t\t\t
rhBMP-2
\n\t\t\t
ACS
\n\t\t\t
Maxillary sinus floor elevation
\n\t\t\t
rhBMP-2/ACS safely induced adequate bone for the placement and functional loading of dental implants
\n\t\t
\n\t\t
\n\t\t\t
Herford and Boyne 2008 [75]
\n\t\t\t
Case review
\n\t\t\t
14
\n\t\t\t
rhBMP-2
\n\t\t\t
ACS
\n\t\t\t
Mandibular defect
\n\t\t\t
Bone formation could be identified radiographically after 5 to 6 months
\n\t\t
\n\t\t
\n\t\t\t
Van den Bergh et al. 2000 [76]
\n\t\t\t
\n\t\t\t
3
\n\t\t\t
rhBMP-2
\n\t\t\t
Type I collagen
\n\t\t\t
Maxillary sinus floor elevation
\n\t\t\t
Potential for initiating bone formation in the human maxillary sinus within 6 months after a sinus floor elevation, but its behavior is currently not sufficiently predictable in this application
\n\t\t
\n\t\t
\n\t\t\t
Kao et al., 2012 [56]
\n\t\t\t
Clinical trial
\n\t\t\t
\n\t\t\t
rhBMP-2
\n\t\t\t
ACS and xenogenic bone
\n\t\t\t
Sinus floor elevation
\n\t\t\t
Less bone formed in patients treated with the rhBMP-2/ACS/xenogenic bone device
\n\t\t
\n\t\t
\n\t\t\t
Alonso et al. 2010 [89]
\n\t\t\t
RCT
\n\t\t\t
16
\n\t\t\t
rhBMP-2
\n\t\t\t
Collagen
\n\t\t\t
Alveolar defect closure in cleft lip and palate patients
\n\t\t\t
Satisfactory bone healing at 6 months and reduced morbidity
\n\t\t
\n\t\t
\n\t\t\t
Stavropoulos et al. 2011 [63]
\n\t\t\t
RCT
\n\t\t\t
20
\n\t\t\t
rhGDF-5
\n\t\t\t
β-TCP
\n\t\t\t
Regeneration of periodontal defects
\n\t\t\t
Greater alveolar regeneration, differences not statistically significant
\n\t\t
\n\t\t
\n\t\t\t
Nevins et al. 2011 [49]
\n\t\t\t
Cohort study
\n\t\t\t
\n\t\t\t
rhPDGF
\n\t\t\t
Mineral collagen scaffold
\n\t\t\t
Socket preservation
\n\t\t\t
No statistically significant differences were observed
\n\t\t
\n\t\t
\n\t\t\t
Stavropoulos et al. 2011 [58]
\n\t\t\t
RCT
\n\t\t\t
31
\n\t\t\t
rhGDF-5
\n\t\t\t
TCP
\n\t\t\t
Sinus floor elevation
\n\t\t\t
Comparable amount and similar quality of bone formation as in controls
\n\t\t
\n\t\t
\n\t\t\t
Jayakumar et al. 2011 [65]
\n\t\t\t
RCT
\n\t\t\t
54
\n\t\t\t
rhPDGF
\n\t\t\t
TCP
\n\t\t\t
Regeneration of periodontal defects
\n\t\t\t
Increased bone formation and soft tissue healing
\n\t\t
\n\t\t
\n\t\t\t
McAllister et al. 2010 [85]
\n\t\t\t
RCT
\n\t\t\t
12
\n\t\t\t
rhPDGF
\n\t\t\t
β-TCP
\n\t\t\t
Socket preservation
\n\t\t\t
Similar histological findings at 3 months
\n\t\t
\n\t\t
\n\t\t\t
Triplett et al. 2009 [55]
\n\t\t\t
RCT
\n\t\t\t
160
\n\t\t\t
rhBMP-2
\n\t\t\t
ACS
\n\t\t\t
Sinus floor elevation
\n\t\t\t
Induced bone was significantly denser, no marked differences in histological parameters.
\n\t\t
\n\t
Table 3.
Clinical studies on GF delivery systems applicable in oral surgery
4.7. Gene delivery methods
The potential applications of gene therapy have recently expanded to include the local treatment of bone defects. Gene transfer methods may circumvent many of the weaknesses of protein delivery to soft tissue wounds. The application of growth factors or soluble forms of cytokine receptors by means of gene transfer offers a greater sustainability than the use of a single protein application. Gene therapy may make growth factors more readily bio-available.
Gene transfer is accomplished by using viral and non-viral vectors. Examples of viral vectors are retroviruses, adenoviruses (Ads), and adeno-associated viruses (AAV), and non-viral vectors include plasmids and DNA polymer complexes.
Some authors have studied gene delivery via adenoviral or liposomal vectors carrying information for encoding recombinant human GFs combined with a collagen matrix in animal models [87,88].
5. Conclusion
The role of growth factors for alveolar bone regeneration in dentistry is a recent field of research, with a relative paucity of clinical studies. Findings seem to demonstrate a positive effect of GFs on intraoral hard and soft tissues healing, and the bone regeneration associated with implant therapy represents one of the main scenarios of interest. For the time being, however, the application of GFs in this field is limited by the dubious results, complications and side effects encountered so far. In particular, one of the main problems seems to be the relationship between the GF delivery and the timing of the healing process. Among the delivery systems tested to date, only collagen matrices have correlated with successful clinical results, albeit with some limitations. Other potential delivery systems have been studied only in a few animal models, and the currently available data are not enough for any final conclusions to be drawn. The development of dedicated and more “sophisticated” GF delivery systems is probably the most interesting area of research for the future.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/44667.pdf",chapterXML:"https://mts.intechopen.com/source/xml/44667.xml",downloadPdfUrl:"/chapter/pdf-download/44667",previewPdfUrl:"/chapter/pdf-preview/44667",totalDownloads:2937,totalViews:285,totalCrossrefCites:3,totalDimensionsCites:6,totalAltmetricsMentions:0,impactScore:4,impactScorePercentile:88,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"April 26th 2012",dateReviewed:"December 19th 2012",datePrePublished:null,datePublished:"May 22nd 2013",dateFinished:"May 11th 2013",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/44667",risUrl:"/chapter/ris/44667",book:{id:"3361",slug:"regenerative-medicine-and-tissue-engineering"},signatures:"Stefano Sivolella, Marleen De Biagi, Giulia Brunello, Sara Ricci,\nDrazen Tadic, Christiane Marinc, Diego Lops, Letizia Ferroni, Chiara\nGardin, Eriberto Bressan and Barbara Zavan",authors:[{id:"60088",title:"Dr.",name:"Barbara",middleName:null,surname:"Zavan",fullName:"Barbara Zavan",slug:"barbara-zavan",email:"barbara.zavan@unipd.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"60818",title:"Dr.",name:"Stefano",middleName:null,surname:"Sivolella",fullName:"Stefano Sivolella",slug:"stefano-sivolella",email:"stefano.sivolella@libero.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Padua",institutionURL:null,country:{name:"Italy"}}},{id:"97030",title:"Dr.",name:"Letizia",middleName:null,surname:"Ferroni",fullName:"Letizia Ferroni",slug:"letizia-ferroni",email:"letizia.ferroni@unipd.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Padua",institutionURL:null,country:{name:"Italy"}}},{id:"99681",title:"Prof.",name:"Eriberto",middleName:null,surname:"Bressan",fullName:"Eriberto Bressan",slug:"eriberto-bressan",email:"eriberto.bressan@unipd.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Padua",institutionURL:null,country:{name:"Italy"}}},{id:"156962",title:"Dr.",name:"Chiara",middleName:null,surname:"Gardin",fullName:"Chiara Gardin",slug:"chiara-gardin",email:"chiara.gardin@unipd.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"164813",title:"Dr.",name:"Marleen",middleName:null,surname:"De Biagi",fullName:"Marleen De Biagi",slug:"marleen-de-biagi",email:"marleen.debiagi@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"164814",title:"Dr.",name:"Giulia",middleName:null,surname:"Brunello",fullName:"Giulia Brunello",slug:"giulia-brunello",email:"giulia-bru@libero.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"167722",title:"Dr.",name:"Sara",middleName:null,surname:"Ricci",fullName:"Sara Ricci",slug:"sara-ricci",email:"sararicci04@hotmail.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"167723",title:"Mrs.",name:"Federica",middleName:null,surname:"Berto",fullName:"Federica Berto",slug:"federica-berto",email:"fede_pd2004@libero.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"167724",title:"Dr.",name:"Diego",middleName:null,surname:"Lops",fullName:"Diego Lops",slug:"diego-lops",email:"lops2@libero.it",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"167725",title:"Dr.",name:"Drazen",middleName:null,surname:"Tadic",fullName:"Drazen Tadic",slug:"drazen-tadic",email:"Drazen.Tadic@botiss.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"167726",title:"Dr.",name:"Christiane",middleName:null,surname:"Marinc",fullName:"Christiane Marinc",slug:"christiane-marinc",email:"Christiane.Marinc@botiss.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Mechanism of action of growth factors (GFs)",level:"1"},{id:"sec_3",title:"3. Clinical application of GFs in dentistry",level:"1"},{id:"sec_3_2",title:"3.1. Pre-prosthetic surgery for the purpose of dental rehabilitation with implants",level:"2"},{id:"sec_4_2",title:"3.2. Dental implant surface coatings with GFs ",level:"2"},{id:"sec_5_2",title:"3.3. Maxillary sinus lift procedure ",level:"2"},{id:"sec_6_2",title:"3.4. Periodontal regeneration",level:"2"},{id:"sec_8",title:"4. Growth factor delivery systems",level:"1"},{id:"sec_8_2",title:"4.1. Collagen ",level:"2"},{id:"sec_9_2",title:"4.2. Alginate and chitosan",level:"2"},{id:"sec_10_2",title:"4.3. Hyaluronic acid",level:"2"},{id:"sec_11_2",title:"4.4. Hydroxyapatite",level:"2"},{id:"sec_12_2",title:"4.5. Synthetic biodegradable polymers",level:"2"},{id:"sec_13_2",title:"4.6. Bone grafts and derived composite materials",level:"2"},{id:"sec_14_2",title:"4.7. 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A combination of platelet-derived and insulin-like growth factors enhances periodontal regeneration. Journal of Clinical Periodontology 1989;16(8):545–8. '},{id:"B20",body:'Al-Hazmi BA, Al-Hamdan KS, Al-Rasheed A, Babay N, Wang HL, Al-Hezaimi K. Efficacy of Using Platelet Derived Growth Factor and Xenograft (With or Without Collagen Membrane) for Bone Regeneration Around Immediate Implants With Induced Dehiscence Type Defects: A Micro-Computed Tomographic Study in Dogs. Journal of Periodontology 2012. [Epub ahead of print]'},{id:"B21",body:'Shah P, Keppler L, Rutkowski J. A review of Platelet Derived Growth Factor playing pivotal role in bone regeneration. Journal of Oral Implantology 2012 Apr 19. [Epub ahead of print]'},{id:"B22",body:'Ishii Y, Fujita T, Okubo N, Ota M, Yamada S, Saito A. Effect of basic fibroblast growth factor (FGF-2) in combination with beta tricalcium phosphate on root coverage in dog. Acta Odontologica Scandinavica 2012 May 1. 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Head and Face Medicine 2011;7:13.'},{id:"B27",body:'Teare JA, Petit JC, Ripamonti U. Synergistic induction of periodontal tissue regeneration by binary application of human osteogenic protein-1 and human transforming growth factor-β(3) in Class II furcation defects of Papio ursinus. Journal of Periodontal Research 2012;47(3):336–44. '},{id:"B28",body:'Lossdörfer S, Abuduwali N, Jäger A. Bone morphogenetic protein-7 modifies the effects of insulin-like growth factors and intermittent parathyroid hormone (1-34) on human periodontal ligament cell physiology in vitro. Journal of Periodontoly 2011;82(6):900–8.'},{id:"B29",body:'Esposito M, Grusovin MG, Felice P, Karatzopoulos G, Worthington HV, Coulthard P. Interventions for replacing missing teeth: horizontal and vertical bone augmentation techniques for dental implant treatment. Cochrane Database of Systematic Reviews 2009;(4):CD003607.'},{id:"B30",body:'Tonetti MS, Hämmerle CHF. Advances in bone augmentation to enable dental implant placement: Consensus Report of the Sixth European Workshop on Periodontology. Journal of Clinical Periodontology 2008;35(Suppl. 8):168–72.'},{id:"B31",body:'Kao DW, Fiorellini JP. Regenerative periodontal therapy. Frontiers of Oral Biology 2012;15:149–59. '},{id:"B32",body:'Chiapasco M, Zaniboni M, Clinical outcomes of GBR procedures to correct peri-implant dehiscences and fenestrations: a systematic review. Clinical Oral Implants Research 2009;20 Suppl 4:113–23.'},{id:"B33",body:'Haidar ZS, Hamdy RC, Tabrizian M. Delivery of recombinant bone morphogenetic proteins for bone regeneration and repair. Part A: Current challenges in BMP delivery. Biotechnology Letters 2009;31(12):1817–24. '},{id:"B34",body:'Park JB. Use of bone morphogenetic proteins in sinus augmentation procedure. Journal of Craniofacial Surgery 2009;20(5):1501–3.'},{id:"B35",body:'Wikesjö UM, Qahash M, Huang YH, Xiropaidis A, Polimeni G, Susin C. Bone morphogenetic proteins for periodontal and alveolar indications; biological observations – clinical implications. Orthodontics and Craniofac Research 2009;12(3):263–70.'},{id:"B36",body:'Howell TH, Fiorellini J, Jones A, Alder M, Nummikoski P, Lazaro M, Lilly L, Cochran D. A feasibility study evaluating rhBMP-2/absorbable collagen sponge device for local alveolar ridge preservation or augmentation. The International Journal of Periodontics and Restorative Dentistry 1997;17(2):124–39.'},{id:"B37",body:'Bianchi J, Fiorellini JP, Howell TH, Sekler J, Curtin H, Nevins ML, Friedland B. Measuring the efficacy of rhBMP-2 to regenerate bone: a radiographic study using a commercially available software program. The International Journal of Periodontics and Restorative Dentistry 2004;24(6):579–87.'},{id:"B38",body:'Boyne PJ, Lilly LC, Marx RE, Moy PK, Nevins M, Spagnoli DB, Triplett RG. De novo bone induction by recombinant human bone morphogenetic protein-2 (rhBMP-2) in maxillary sinus floor augmentation. Journal of Oral and Maxillofacial Surgery 2005;63(12):1693-707.'},{id:"B39",body:'Fiorellini JP, Howell TH, Cochran D, Malmquist J, Lilly LC, Spagnoli D, Toljanic J, Jones A, Nevins M. Randomized study evaluating recombinant human bone morphogenetic protein-2 for extraction socket augmentation. Journal of Periodontology 2005;76(4):605–13.'},{id:"B40",body:'Jung RE, Glauser R, Scharer P, Hammerle CH, Sailer H, Weber FE. Effect of rhBMP-2 on guided bone regeneration in humans. Clinical Oral Implants Research 2003;14(5):556–68.'},{id:"B41",body:'Boyne P J, Marx RE, Nevins M, Triplett G, Lazaro E, Lilly LC, Alder M, Nummikoski P. A feasibility study evaluating rhBMP-2/absorbable collagen sponge for maxillary sinus floor augmentation. The International Journal of Periodontics and Restorative Dentistry 1997;17(1):11–25.'},{id:"B42",body:'Misch CM. Bone augmentation of the atrophic posterior mandible for dental implants using rhBMP-2 and titanium mesh: clinical technique and early results. The International Journal of Periodontics and Restorative Dentistry 2011;31(6):581–9.'},{id:"B43",body:'Sigurdsson TJ, Nguyen S, Wikesjö UM. Alveolar ridge augmentation with rhBMP-2 and bone-to-implant contact in induced bone. The International Journal of Periodontics and Restorative Dentistry 2001;21(5):461–73.'},{id:"B44",body:'Wikesjö UM, Qahash M, Thomson RC, Cook AD, Rohrer MD, Wozney JM, Hardwick WR. Space-providing expanded polytetrafluoroethylene devices define alveolar augmentation at dental implants induced by recombinant human bone morphogenetic protein-2. Clinical Implant Dentistry and Related Research 2003;5(2):112–23.'},{id:"B45",body:'Jung RE, Windisch SI, Eggenschwiler AM, Thoma DS, Weber FE, Hämmerle CH. A randomized-controlled clinical trial evaluating clinical and radiological outcomes after 3 and 5 years of dental implants placed in bone regenerated by means of GBR techniques with or without the addition of BMP-2. Clinical Oral Implants Research 2009;20(7):660–6.'},{id:"B46",body:'Simion M, Nevins M, Al-Hezaimi K, et al. Vertical ridge augmentation using an equine bone and collagen block infused with recombinant human platelet derived growth factor-BB (rhPDGF-BB): A randomized single-blind histologic study in non-human primates. Journal of Periodontology 2012. [Epub ahead of print]'},{id:"B47",body:'Nevins ML, Camelo M, Schupbach P, Kim DM, Camelo JM, Nevins M. Human histologic evaluation of mineralized collagen bone substitute and recombinant platelet-derived growth factor- BB to create bone for implant placement in extraction socket defects at 4 and 6 months: a case series. The International Journal of Periodontics and Restorative Dentistry 2009;29(2):129–39. '},{id:"B48",body:'Simion M, Rocchietta I, Dellavia C. Three-dimensional ridge augmentation with xenograft and recombinant human platelet-derived growth factor-BB in humans: report of two cases. The International Journal of Periodontics and Restorative Dentistry 2007;27(2):109–15. '},{id:"B49",body:'Nevins ML, Camelo M, Schupbach P, Nevins M, Kim SW, Kim DM. Human buccal plate extraction socket regeneration with recombinant human platelet-derived growth factor BB or enamel matrix derivative. The International Journal of Periodontics and Restorative Dentistry 2011;31(5):481–92.'},{id:"B50",body:'Susin C, Qahash M, Polimeni G, Lu PH, Prasad HS, Rohrer MD, Hall J, Wikesjö UM. Alveolar ridge augmentation using implants coated with recombinant human bone morphogenetic protein-7 (rhBMP-7/rhOP-1): histological observations. Journal of Clinical Periodontology 2010;37(6): 574–81.'},{id:"B51",body:'Polimeni G, Wikesjö UM, Susin C, Qahash M, Shanaman RH, Prasad HS, Rohrer MD, Hall J. Alveolar ridge augmentation using implants coated with recombinant human growth/differentiation factor-5: histologic observations. Journal of Clinical Periodontology 2010;37(8):759–68.'},{id:"B52",body:'Leknes KN, Yang J, Qahash M, Polimeni G, Susin C, Wikesjö UM. Alveolar ridge augmentation using implants coated with recombinant human growth/differentiation factor-5 (rhGDF-5). Radiographic observations. Clinical Oral Implants Research 2012 Aug 6. [Epub ahead of print]'},{id:"B53",body:'Jensen OT, Shulman LB, Block MS, Iacono VJ. (1998) Report of the sinus consensus conference of 1996. The International Journal of Oral and Maxillofacial Implants 1998;13 Suppl:11–45.'},{id:"B54",body:'Ho SKC, Peel SAF, Hu ZM, Sándor GKB, Clokie CML. Augmentation of the Maxillary Sinus: Comparison of Bioimplants Containing Bone Morphogenetic Protein and Autogenous Bone in a Rabbit Model. Journal of the Canadian Dental Association 2010;76:a108.'},{id:"B55",body:'Triplett RG, Nevins M, Marx RE, Spagnoli DB, Oates TW, Moy PK, Boyne PJ. Pivotal, Randomized, Parallel Evaluation of Recombinant Human Bone Morphogenetic Protein-2/Absorbable Collagen Sponge and Autogenous Bone Graft for Maxillary Sinus Floor Augmentation. Journal of Oral Maxillofacial Surgery 2009;67(9):1947–60. '},{id:"B56",body:'Kao DW, Kubota A, Nevins M, Fiorellini JP. The negative effect of combining rhBMP-2 and Bio-Oss on bone formation for maxillary sinus augmentation. The International Journal of Periodontics and Restorative Dentistry 2012;32(1):61–7.'},{id:"B57",body:'Gruber RM, Ludwig A, Merten HA, Achilles M, Poehling S, Schliephake H. Sinus floor augmentation with recombinant human growth and differentiation factor-5 (rhGDF-5): a histological and histomorphometric study in the Goettingen miniature pig. Clinical Oral Implants Research 2008;19(5):522–9.'},{id:"B58",body:'Stavropoulos A, Becker J, Capsius B, Açil Y, Wagner W, Terheyden H. Histological evaluation of maxillary sinus floor augmentation with recombinant human growth and differentiation factor-5-coated β-tricalcium phosphate: results of a multicenter randomized clinical trial. Journal of Clinical Periodontology 2011;38(10):966–74.'},{id:"B59",body:'Kitamura M, Akamatsu M, Machigashira M, Hara Y, Sakagami R, Hirofuji T, Hamachi T, Maeda K, Yokota M, Kido J, Nagata T, Kurihara H, Takashiba S, Sibutani T, Fukuda M, Noguchi T, Yamazaki K, Yoshie H, Ioroi K, Arai T, Nakagawa T, Ito K, Oda S, Izumi Y, Ogata Y, Yamada S, Shimauchi H, Kunimatsu K, Kawanami M, Fujii T, Furuichi Y, Furuuchi T, Sasano T, Imai E, Omae M, Yamada S, Watanuki M, Murakami S. FGF-2 Stimulates Periodontal Regeneration: Results of a Multi-center Randomized Clinical Trial. Journal of Dental Research 2011;90(1):35-40.'},{id:"B60",body:'Ripamonti U, Petit J-C. Bone morphogenetic proteins, cementogenesis, myoblastic stem cells and the induction of periodontal tissue regeneration. Cytokine & Growth Factor Reviews 2009; 20(5-6):489–99. '},{id:"B61",body:'Ripamonti U, Ferretti C, Teare J, Blann L. Transforming growth factor-beta isoforms and the induction of bone formation: implications for reconstructive craniofacial surgery. Journal of Craniofacial Surgery 2009;20(5):1544–55.'},{id:"B62",body:'Kim YT, Wikesjö UM, Jung UW, Lee JS, Kim TG, Kim CK. Comparison Between a β-Tricalcium Phosphate and an Absorbable Collagen Sponge Carrier Technology for Recombinant Human Growth/Differentiation Factor-5 Stimulated Periodontal Wound Healing/Regeneration. Journal of Periodontology 2012 Aug 16. [Epub ahead of print]'},{id:"B63",body:'Stavropoulos A, Windisch P, Gera I, Capsius B, Sculean A, Wikesjö UM. A phase IIa randomized controlled clinical and histological pilot study evaluating rhGDF-5/b-TCP for periodontal regeneration. Journal of Clinical Periodontology 2011;38(11):1044–54.'},{id:"B64",body:'Howell TH, Fiorellini JP, Paquette DW, Offenbacher S, Antoniades HN, Lynch SE. Evaluation of a combination of recombinant human platelet-derived growth factor-BB and recombinant human insulin-like growth factor-I in patients with periodontal disease. Journal of Dental Research 1995;74:253. '},{id:"B65",body:'Jayakumar A, Rajababu P, Rohini S, Butchibabu K, Naveen A, Krishnajaneya Reddy P, Vidyasagar S, Satyanarayana D, Pavan Kumar S. Multi-centre, randomized clinical trial on efficacy and safety of recomb-inant human platelet-derived growth factor with b-tricalcium phosphate in human intra-osseous periodontal defects. Journal of Clinical Periodontology 2011;38(2):163–72. '},{id:"B66",body:'Senta H, Park H, Bergeron E, Drevelle O, Fong D, Leblanc E, Cabana F, Roux S, Grenier G, Faucheux N. Cell responses to bone morphogenetic proteins and peptides derived from them: biomedical applications and limitations. Cytokine and Growth Factor Reviews 2009 Jun;20(3):213–22. '},{id:"B67",body:'Mont MA, Ragland PS, Biggins B, Friedlaender G, Patel T, Cook S, Etienne G, Shimmin A, Kildey R, Rueger DC, Einhorn TA. Use of bone morphogenetic proteins for musculoskeletal applications. An overview. Journal of Bone and Joint Surgery m. 2004;86:41-55.'},{id:"B68",body:'Dard M, Sewing A, Meyer J, Verrier S, Roessler S, Scharnweber D. Tools for tissue engineering of mineralized oral structures. Clinical Oral Investigations 2000 Jun;4(2):126–9.'},{id:"B69",body:'Giannoudis PV, Psarakis S, Kanakaris NK, Pape HC. Biological enhancement of bone healing with Bone Morphogenetic Protein-7 at the clinical setting of pelvic girdle non-unions. Injury 2007 Sep;38:S43–8.'},{id:"B70",body:'Benglis D, Wang MY, Levi AD. A comprehensive review of the safety profile of bone morphogenetic protein in spine surgery. Neurosurgery 2008;62:431-32.'},{id:"B71",body:'Uludag H, Gao T, Porter TJ, Friess W, Wozney JM. Delivery systems for BMPs: factors contributing to protein retention at an application site. Journal of Bone and Joint Surgery 2001;83:S128–35.'},{id:"B72",body:'Jeon O, Song SJ, Yang HS, Bhang SH, Kang SW, Sung MA, Lee JH, Kim BS. Long-term delivery enhances in vivo osteogenic efficacy of bone morphogenetic protein-2 compared to short-term delivery. Biochemical and Biophysical Research Communications 2008 May 2;369(2):774–80.'},{id:"B73",body:'Haidar ZS, Hamdy RC, Tabrizian M. Delivery of recombinant bone morphogenetic proteins for bone regeneration and repair. Part B: Delivery systems for BMPs in orthopaedic and craniofacial tissue engineering. Biotechnology Letters 2009;31:1825-1835.'},{id:"B74",body:'Okafuji N, Shimizu T, Watanabe T, Kimura A, Kurihara S, Arai Y, Furusawa K, Hasegawa H, Kawakami T. Three-dimensional observation of reconstruction course of rabbit experimental mandibular defect with rhBMP-2 and atelocollagen gel. European Journal of Medical Research 2006 Aug 30;11(8):351–4.'},{id:"B75",body:'Herford AS, Boyne PJ. Reconstruction of mandibular continuity defects with bone morphogenetic protein-2 (rh BMP-2). Journal of Oral and Maxillofacial Surgery 2008;66:616-624.'},{id:"B76",body:'van den Bergh JP, Ten Bruggenkate CM, Groeneveldt et al. recombinant human bone morphogenetic protein-7 in maxillary sinus floor elevation surgery in 3 patients compared to autogenous bone grafts. A clinical pilot study. Journal of Clinical Periodontology 2000;27:627-636.'},{id:"B77",body:'Lim SM, Oh SH, Lee HH, Yuk SH, Im GI, Lee JH. Dual growth factor-releasing nanoparticle/hydrogel system for cartilage tissue engineering. Journal of Materials Science: Materials in Medicine. 2010 Sep;21(9):2593–600.'},{id:"B78",body:'Issa JP, Bentley MV, Iyomasa MM, Sebald W, De Albuquerque RF. Sustained release carriers used to delivery bone morphogenetic proteins in the bone healing process. Anatomia, Histologia, Embryologia. 2008 Jun;37(3):181-7.'},{id:"B79",body:'Arosarena OA, Collins WL. Bone regeneration in the rat mandible with bone morphogenetic protein-2: a comparison of two carriers. Otolaryngology – Head and Neck Surgery. 2005 Apr;132(4):592-7.'},{id:"B80",body:'Li RH, Wozney JM. Delivering on the promise of bone morphogenetic proteins. Trends in Biotechnology. 2001 Jul;19(7):255–65.'},{id:"B81",body:'Kim SS, Gwak SJ, Kim BS. Orthotopic bone formation by implantation of apatite-coated poly(lactide-co-glycolide)/hydroxyapatite composite particulates and bone morphogenetic protein-2. Journal of Biomedical Materials Research 2008;87:245-253.'},{id:"B82",body:'Schopper C, Moser D, Spassova E et al. Bone re generation using a naturally grown HA/TCP carrier loaded with rh BMP-2 is independent of barrier-membrane effects. Journal of Biomedical Materials Research 2008;85:954-963.'},{id:"B83",body:'Zellin G, Linde A. importance of delivery systems for growth-stimulatory factors in combination with osteopromotive membranes. An experimental study using rhBMP-2 in rat mandibular defects. Journal of Biomedical Materials Research 1997;35:181-190.'},{id:"B84",body:'Albrektsson T, Johansson C. Osteoinduction, osteoconduction and osseointegration. European Spine Journal 2001 Oct;10 Suppl 2:S96–101.'},{id:"B85",body:'McAllister BS, Haghighat K, Prasad HS, Rohrer MD. Histologic evaluation of recombinant human platelet-derived growth factor-BB after use in extraction socket defects: a case series. The International Journal of Periodontics and Restorative Dentistry 2010 Aug;30(4):365-73.'},{id:"B86",body:'Liu Y, Enggist L, Kuffer AF, Buser D, Hunziker EB. The influence of BMP-2 and its mode of delivery on the osteoconductivity of implant surfaces during the early phase of osseointegration. Biomaterials. 2007 Jun;28(16):2677-86.'},{id:"B87",body:'Lutz R, Park J, Felszeghy E, Wiltfang J, Nkenke E, Schlegel KA. Bone regeneration after topical BMP-2-gene delivery in circumferential peri-implant bone defects. Clinical Oral Implants Research 2008 Jun;19(6):590-9.'},{id:"B88",body:'Chang SC, Lin TM, Chung HY, Chen PK, Lin FH, Lou J, Jeng LB. Large-scale bicortical skull bone regeneration using ex vivo replication-defective adenoviral-mediated bone morphogenetic protein-2 gene-transferred bone marrow stromal cells and composite biomaterials. Neurosurgery. 2009 Dec;65(6 Suppl):75-81.'},{id:"B89",body:'Alonso N, Tanikawa DY, Freitas S et al. Evaluation of maxillary alveolar reconstruction using a resorbable collagen sponge with recombinant human bone morphogenetic protein-2 in cleft lip and palate patients. Tissue Engineering Part C: Methods 2010;16:1183-9.'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Stefano Sivolella",address:"stefano.sivolella@libero.it",affiliation:'
Department of Oral Surgery, University of Padova, Institute of Clinical Dentistry, Padova, Italy
'},{corresp:null,contributorFullName:"Marleen De Biagi",address:null,affiliation:'
Department of Oral Surgery, University of Padova, Institute of Clinical Dentistry, Padova, Italy
Scatterometers are non-imaging active sensors used to measure the intensity of microwave backscatter while scanning the surface of the earth from an aircraft or a satellite. Active microwave sensors are radars providing their own illumination and do not depend upon ambient radiation like passive microwave sensors. They transmit microwave electromagnetic pulses toward the surface and measure how much of that signals return after interacting with the target. Scatterometer is a form of radar that is used to investigate different geophysical properties of the surface and few centimeters beneath. Spaceborne scatterometers have the advantage of providing global coverage on a continuous basis, which cannot be achieved through airborne or ground measurements. They have the capability of providing day and night time measurements unaffected by cloud cover. Scatterometers were originally designed to study ocean winds but have been also used to study of cryosphere, vegetation, and soil surface properties.
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A number of scatterometers have been flown on space missions since the early 1970s. The first scatterometer in space was a Ku-band instrument on Skylab mission. Investigations on the potential use of scatterometers in geosciences achieved a major technical milestone with the launch of Seasat, carrying a Ku-band scatterometer (SASS), in 1978. Other missions have followed SASS; C-band scatterometers onboard the European Space Agency’s (ESA) Earth Remote Sensing (ERS 1 & ERS-2) satellites in 1991 and 1995, the NASA’s Ku-band scatterometer (NSCAT) in 1996, SeaWinds on QuikSCAT in 1999, SeaWinds on ADEOS-II in 2002, and Advanced Scatterometer (ASCAT) onboard Metop-A launched in 2006.
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In this study we focus on spaceborne C-band scatterometers and present an overview of their applications in geoscience.
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2. C-band Scatterometers
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2.1. SCAT onboard ERS satellites
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The first spaceborne C-band scatterometer was flown on ERS-1, the European Earth observation mission. ERS-1, launched in July 1991, was aimed to provide environmental monitoring particularly in the microwave spectrum. ERS-1 has been placed in a near-polar orbit at a mean altitude of about 780km with an instrument payload comprising active and passive microwave sensors and a thermal infra-red radiometer. ERS-2 the follow-up ESA mission of ERS-1 was launched in 1995. The ERS-2 satellite is a copy of ERS-1 except that it includes a number of enhancements and new payload instruments. Both scatterometers onboard ERS-1 and ERS-2 are part of an Active Microwave Instrument (AMI) operating in C-band (5.3 GHz). The AMI incorporates two separate radar systems; Synthetic Aperture Radar (SAR) and scatterometer (SCAT) operating in three different modes. SAR for Image and Wave mode operations, and scatterometer for Wind mode operation. The Wind and Wave modes are capable of interleaved operation, i.e. so-called Wind/Wave mode, but the operation in Image mode excludes the operation of the other two modes (Attema, 1991).
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2.2. ASCAT onboard Metop satellites
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The Advanced Scatterometer (ASCAT) is the new generation and successor of the ERS SCATs onboard the Meteorological Operational (Metop) series of satellites. Metop-A, launched on 19 October 2006, is the first satellite in the series foreseen in EUMETSAT Polar System (EPS) program (Klaes et al., 2007). Like SCAT, ASCAT system uses a fan-beam antenna technology and transmits vertically polarized pulses at frequency of 5.255 GHz with high radiometric stability. Contrary to SCAT it uses two sets of three antennas instead
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Figure 1.
Viewing geometries of the scatterometers onboard ERS and Metop satellites.
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of one. For ASCAT the incidence angle range has been extended from 25 to 65 . Hence ASCAT covers two 550 km swaths to the left and right of the satellite ground track which are separated from the satellite ground track by about 336 km. This results in over twice faster global-coverage capability than its predecessor SCAT. Beside an optimized viewing geometry, ASCAT also features a number of technical improvements. The improved instrument design and radiometric performance results in higher stability and reliability of ASCAT measurements. Additionally EUMETSAT foresees to generate a research product at a resolution of 25km (Figa-Saldana et al., 2002). Figure 1 illustrates the viewing geometries of SCAT and ASCAT. Specifications of the C-band scatterometers and their carrier satellites are given in table-1.
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Satellite Specifications
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ERS-1
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ERS-2
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Metop-A
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Launch Time
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17 July 1991
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21 April 1995
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19 October 2006
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Launch Mass
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2354 kg
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2516 kg
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4093 kg
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launcher
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Ariane 4
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Soyuz/ST
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Spacecraft Altitude
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770 to 785 km
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800 to 850 km
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Inclination
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98.52°
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98.7°
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Local Solar Time
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10:30 am*
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9:30 am*
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Orbit Period
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100 minutes
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101 minutes
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Orbit
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Near-circular, polar, Sun-synchronous
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Scatterometer Specifications
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SCAT
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ASCAT
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Frequency
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5.3 GHz. (C-Band)
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5.255 GHz. (C-Band)
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Polarization
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VV
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VV
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Swath Width
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500 km
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550 km (double swath)
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Swath Stand-off
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200 km to the right of sub-satellite track
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336 km
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Localization Accuracy
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5 km
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4.4 km
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Spatial Resolution
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50 km
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50 km, 25 km
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Sampling Interval
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25 km
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25 km, 12.5 km
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* equatorial crossing time at the descending node
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Table 1.
Specifications of the European C-band scatterometers.
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3. Wind Speed and Direction Measurement
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The primary application of the spaceborne scatterometry has been the measurement of near-surface winds over the ocean. The concept of retrieving wind speed at sea surface from the radar backscatter goes back to the Second World War. During the World War II, marine radar operators observed disturbing noises, called “clutter”, on their radar screens, which made them difficult detecting targets on the ocean surface (Moore et al., 1979). The clutters were the backscatter of the radar pulses from the small waves on the sea surface. Since that time many theoretical studies and experiments have been carried out to find the relationship between the microwave backscatter and the surface wind speed (Liu, 2002). The idea of remote sensing of the wind relies on the fact that winds over the sea cause small-scale disturbances of the sea surface which modify the radar backscattering characteristics. The backscatter from oceans is largely due to these small centimeter ripples, capillary waves, which is in equilibrium with the local wind stress. The backscatter depends not only on the magnitude of the wind stress but also the wind direction relative to the direction of the radar beam. By combining backscatter measurements from different azimuth angles, the near-surface wind vector over the ocean\'s surface can be determined using a Geophysical Model Function (GMF). The first operational GMF used for ERS-1 scatterometer data by ESA was a prelaunch transfer function denoted CMOD2, derived from aircraft-mounted instrument data (Long, 1985). An improved transfer function, CMOD4 was presented by Stoffelen et al. (1997) with full specification. CMOD4 adopted by ESA since March 1993 for wind retrieval. The latest C-band GMF used for wind retrieval is CMOD5, which is derived on the basis of measurements from the ERS-2 scatterometer. The CMOD5 algorithm corrects some shortcomings in the earlier models and result in a better wind retrieval at high wind speed and more uniform performance across the scatterometer swath (Hersbach et al., 2007). The estimated accuracy of the ASCAT 50-km wind product is 2 m/s RMS difference in wind vector components and 0.5 m/s bias in wind speed (ASCAT product guide). The wind observations at sea surface are essential to describe the atmospheric flow and therefore have many meteorological and oceanographic applications. Wind information is useful for weather forecasting, prediction of extreme events, and climate studies. Figure 2 indicates two examples of the ASCAT 25- and 12.5-km wind products (Verhoef et al., 2009). Processing of the wind product is done in near-real time at EUMETSAT’s processing facility. From the sensing time, it takes approximately 2 hours to get the corresponding wind product ready at KNMI. The wind data are disseminated through the EUMETCast system (EUMETCast).
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Figure 2.
ASCAT wind product over Atlantic Ocean (55 N-65 N, ~15 West, South of Iceland). Background image shows the infrared cloud image of the METEOSAT9 geostationary satellite. Images are adopted from (Verhoef et al., 2009).
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4. Monitoring Seasonal Dynamics of Vegetation
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The intensity of the backscattered signal over land is affected by roughness, vegetation structure, vegetation water content, and soil moisture. These factors influence the backscattering coefficient \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t on different time scales. At the resolution of the ERS and Metop scatterometers, surface roughness can be in general considered as a temporally invariant parameter. Surface soil moisture changes rapidly within hours to days, contrary to the vegetation canopy and vegetation water content, which vary within several days to weeks. Scattering from the vegetated surface is a complex phenomenon and difficult to model as the volume scattering contributes in total backscattering. Preliminary studies indicated the potential of the C-band scatterometer data for monitoring the seasonal variation of vegetation using multi-temporal analysis (Wismann et al., 1994, Mougin et al., 1995, Frison et al., 1996a, Frison et al., 1996b). Many studies used semi-empirical models to model vegetation effect on backscatter (Magagi et al., 1997, Woodhouse et al., 2000, Jarlan et al., 2003). There have been several canopy scattering models developed to describe \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t in terms of vegetation and soil surface parameters based on a solution of the radiative transfer equation (Attema et al., 1978, Ulaby et al., 1990, Karam et al., 1992, Saatchi et al., 1994). Radiative transfer theory describes the propagation of radiation through a medium affected by absorption, emission and scattering processes (Fung, 1994). But the problem with all complex theoretical scattering models is that their input data requirements are very challenging and for solving the equations many parameters are needed such as leaf diameter, branch length, trunk moisture, and probability functions representing the orientational distribution of leaves, branches, and trunks.
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The incidence angle of scatterometer observations varies from acquisition to acquisition. Since the intensity of backscatter signal strongly depends on the incidence angle, in the most of the multi-temporal vegetation studies using scatterometer data, \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\tmeasurements are averaged over longer periods (e.g. one month) to make \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t measurements comparable. But the averaging procedure does not allow us to distinguish the impact of the soil moisture and vegetation cover on backscatter. Wagner et al. (1999a) used a simple model fitted to scatterometer observations to model the incidence angle dependency of backscatter:
\n\t\t\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\tshows the incidence angle dependency of\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t. Knowing the incidence angle dependency, \n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\tcan be normalized at a reference incidence angle. In this approach \n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t is calculated for each triplet, which contains concurrent measurements representing the same soil moisture condition. Therefore the effect of soil moisture on incidence angle behavior of \n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\tis negligible, if not completely removed from the backscattered signal: \n\t\t\t\t
where the index m stands for the mid-beam and the indices a and f for the aft and fore beam measurements.
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The backscattered energy received by the scatterometer sensor increases with decreasing incidence angle. The rate of backscatter change due to incidence angle variation depends on the surface roughness. Bare soil roughness is basically constant in time but vegetation can have a seasonal influence on the incidence angle dependency behavior of backscatter. With increasing vegetation density, the shape of incidence angle dependency of backscatter changes depending on the type and density of vegetation as well as the orientation of vegetation elements. Having multi-year scatterometer data, the seasonal variation of slope can be extracted for a reference incidence angle (e.g. 40 ). Slope function at 40 , \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t correlates pretty well with the seasonal vegetation change (Naeimi et al., 2009a). Figure 3-top shows slope values globally calculated for the mid of July. Figure 3-bottom illustrates
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Figure 3.
Above: Global slope values in July. Bottom: Comparison of slope function with NDVI in three different areas.
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three examples of \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t from different regions compared with the Normalized Vegetation index (NDVI). The vegetation index data have been derived from a 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI product (Huete et al., 2002). NDVI values are averaged over three years (2000–2002) to estimate the yearly vegetation variation. Depending on land cover type there is a time lag between NDVI and \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t in most regions (Doubkova et al., 2009). This implies the fact that the \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t derived from C-band backscatter observations corresponds to vegetation structure development whereas NDVI represents only greenness of vegetation canopy.
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5. Soil Moisture Change Detection
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As it mentioned in section 4, \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\tis affected over land by surface roughness, vegetation, and soil moisture. The major challenge of extracting soil moisture from scatterometer data is the presence of the other additional factors influencing the signal. Most studies have introduced physical inversion methods describing scattering process to model roughness and vegetation contributions on backscatter signal (Frison et al., 1997, Pulliainen et al., 1998, Woodhouse et al., 2000, Magagi et al., 2001, Jarlan et al., 2002, Zine et al., 2005). Although theoretical models are useful for understanding and interpreting scattering behavior of natural surfaces, the major problems of these retrieval concepts appear to be their complexity and physical validity at large scales. A promising solution to the problems of physically based inversion models is using change detection method rather than using a complex model to describe the full range of parameters influencing the scattering process. Availability of several years of backscatter data, multi-viewing capability, and high temporal sampling rate of scatterometers make them appropriate instruments for change detection methods. The potential of using change detection techniques for active sensors has been demonstrated in several studies (Wagner, 1998, Moeremans et al., 1998, Quesney et al., 2000, Moran et al., 2000, Le Hegarat-Mascle et al., 2002; De Ridder, 2000).
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5.1. TUWien change detection method
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\n\t\t\t\t\tWagner et al., (1999b) presented a change detection method for soil moisture retrieval from ERS scatterometers. A processing algorithm for soil moisture retrieval based on change detection technique has been developed at the Institute of Photogrammetry and Remote Sensing (IPF) of the Vienna University of Technology (TUWien) which will further be referred to as the TUWien method. In the TUWien method soil moisture dynamics are extracted after modeling the behavior of \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t with respect to the surface roughness and the local variability of vegetation and eventually subtracting them from the backscatter signal. In the retrieval algorithm, multi-looking direction ability of scatterometer is used to describe the incidence angle behavior of the backscatter signal as a seasonal function,\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\tθ\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t. The incidence angle dependency of backscatter can be described by the derivatives of \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t at a reference incidence angle (set to 40 ) according to the Taylor series expansion:
\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t′\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\tand\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t″\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, called slope and curvature at 40 , are calculated by fitting a regression line to the obtained local slope values in equation-2 during a certain period of the year. After determination of slope and curvature for each day of year and using the following second-order polynomial equation based on Taylor series, \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\tθ\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\tmeasurements are extrapolated to 40 incidence angle:\n\t\t\t\t\t
Eventually the normalized backscatter \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t is scaled between the lowest and highest values ever measured within the long-term \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t observations, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tw\n\t\t\t\t\t\t\t\t\t\t\te\n\t\t\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\td\n\t\t\t\t\t\t\t\t\t\t\tr\n\t\t\t\t\t\t\t\t\t\t\ty\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t, which represent the driest and wettest conditions:
\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tΘ\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\tcorresponds to the normalized volumetric water content at topmost 2 cm soil surface ranging between 0% and 100% with presumption of linear relationship between \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t40\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t and the surface soil moisture (Ulaby et al., 1982). In addition the TUWien retrieval algorithm includes processing modules for vegetation correction, wet reference correction and soil moisture uncertainty analysis (Naeimi et al., 2009a). An operational processing system based on the TUWien retrieval algorithm is implemented at EUMETSAT to provide near-real time ASCAT soil moisture data (Hasenauer et al., 2006). The data have been made available through the EUMETCast system (EUMETCast). Figure 4 shows SCAT/ASCAT soil moisture time series compared with precipitation data at a grid point located in Lower Austria. An example of global distribution of the mean soil moisture values retrieved from long-term SCAT time series is shown in Figure 5. The spatial variability of the estimated mean of soil moisture is connected to atmospheric-forcing related soil moisture signal. Soil moisture retrieval from scatterometer data has also limitations when the soil is frozen or
Figure 4.
Soil moisture time series retrieved from SCAT and ASCAT data compared with precipitation data in lower Austria
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covered with snow. As soon as the soil freezes the dielectric constant of the soil drops drastically and results in low backscatter. Therefore the backscattering behaviors of dry and frozen soil are similar. The scattering behavior of snow is more complex and depends on the dielectric properties of the ice particles and on their distribution and density. Furthermore, land cover has also impacts on the quality of soil moisture retrieval from scatterometer data. There is a strong response of the azimuthal noise level of backscatter to different land cover types like rainforests, lakes, rivers, floodplains, coastal areas, urban areas, and sand deserts as well as areas with complex topography (Naeimi et al., 2008). An uncertainty analysis module using Monte Carlo error propagation (Naeimi, 2009b) is implemented within the TUWien algorithm which identifies such problematic areas for soil moisture retrieval from scatterometer data.
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Figure 5.
Mean of surface soil moisture retrieved from long-term SCAT time series.
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5.2. Surface soil moisture anomalies
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Anomalies of soil moisture, precipitation, temperature, and vegetation indices are parameters that are used as indicator of extreme weather conditions. Scatterometer soil moisture anomalies can be calculated by comparing the current values with mean and standard deviation values in the same time of year over the long-term ERS/Metop scatterometer time series. Figure 6 illustrates monthly anomalies of ASCAT soil moisture compared with the NDVI anomaly images derived from MODIS data (NASA-EO). The extremely dry conditions are visible in parts of Europe during July 2007 (Figure 6-a). As reported by the authorities the 2007 drought in Moldova was the most severe in living memory. The World Food Program compared its severity to the drought of 1946 during which many Moldovans starved. The Cereal production at that year was down by 63% compared to the year before, and was about 70% lower than the average of the five years before (FAO news). Figure 6-b shows another example of extreme condition, which is evident in ASCAT soil moisture anomalies. The anomalous wet soil in March 2008 in parts of India provided a suitable condition for vegetation growth. By early April 2008, plants throughout the country were responding to the plentiful water supply that led to record of harvest yield in April (NASA-EO).
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5.3. Soil Water index (SWI)
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The C-band scatterometer derived soil moisture represent only top few centimeter of soil. Nevertheless, thanks to the high temporal sampling of scatterometers (about 80% global daily coverage for ASCAT), soil moisture in plant root zone can be estimated by using an infiltration model. Wagner et al. (1999b) proposed a simple two-layer water balance model to estimate profile soil moisture. The remotely sensed topsoil represents the first layer and the second layer extends downwards from the bottom of the surface layer. In this model, the water content of the reservoir layer is described in terms of a Soil Water Index (SWI), which is controlled only by the past soil moisture conditions in the surface layer in a way that the influence of measurements decreases by increasing the time:
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Figure 6.
Examples of the ASCAT soil moisture anomalies showing extreme dry (top) and wet conditions (bottom) compared with NDVI anomalies extracted from MODIS data.
\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tΘ\n\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t(\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t)\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\tis the surface soil moisture measured at time \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tt\n\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t and \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tT\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t is the characteristic time length connected to the depth of reservoir which describes the linkage between the surface layer and the reservoir by:\n\t\t\t\t\t
where \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t is the depth of the reservoir layer and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tC\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t is a pseudo-diffusivity coefficient that depends on soil properties. \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tΘ\n\t\t\t\t\t\t\t\t\t\ts\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\tand \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tΘ\n\t\t\t\t\t\t\t\t\t\tr\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t are the volumetric moisture content of the surface and reservoir respectively.
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Daily images of SWI calculated at five different \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tT\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t values (10, 20, 40, 60, 100) retrieved from ASCAT-25km observations using a near-real time recursive processor will be available through the geoland project (geoland-II). Figure 7 indicates the global ASCAT-50km SWI image calculated for T=10 as an example.
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Figure 7.
ASCAT-50km Soil Water Index (SWI) at T=10.
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6. Monitoring Cryosphere
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The cryosphere consists of the parts of the Earth’s surface where water exists in solid form, including snow cover, frozen ground, glacier, see ice, ice sheets and any other form of ice on land or in ocean. The cryosphere plays an important role in the global climate system and therefore impacts significantly human life. More than about 70% of the Earth’s freshwater is frozen in ocean ice sheets, glaciers or permafrost areas (UNESCO report, 2006). Permafrost regions are of major interest in climate studies as several hundred gigatons of carbon are stored in frozen soils in high latitudes. Thawing of permafrost could supercharge the global warming process. There is also a major concern about the possibility of shrinking the Earth’s ice sheets due to the global warming which could raise the global sea level by several meters. There are many cryosphere-climate feedback mechanisms in the global climate system over a wide range of spatial and temporal scales. Snow and ice have a remarkable effect on climate as they modulate energy exchanges between the surface and the atmosphere because of their physical properties. One of the most important properties is the surface reflectance (albedo). Non-melting snow and ice can reflect between ~80-90% of incident solar energy whereas vegetation and soil surface reflect as little as 20-30%. The reflected sunlight into space does not get absorbed by the Earth as heat. Therefore the high albedo plays as a cooling factor in the global climate system. The thermal properties of cryospheric elements have also major consequences for the climate and hydrological cycle. Snow and ice have much lower thermal diffusivities than air and build an insulating layer over land and ocean surfaces decoupling the surface-atmosphere interface with respect to both heat and moisture fluxes. High latent heat is another thermal property of snow and ice that act to moderate temperature in warm seasons because of the large amount of energy required to melt ice.
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Scatterometry has been proven to be useful for monitoring and understanding the cryosphere. Several studies have investigated the applicability of scatterometer data in various cryosphere research areas for instance; mapping snowmelt extent (Wismann et al., 1997; Wismann, 2000), snow accumulation in Greenland (Drinkwater et al., 2001), snow cover over the Northern Hemisphere (Nghiem et al., 2001), frozen terrain in Alaska (Kimball et al., 2001). Other studies have used scatterometer data for determination of freeze/thaw cycles in Northern Latitudes (Bartsch et al., 2007), spatial and temporal variability of sea ice (Drinkwater et al., 2000), classification of sea ice in Polar Regions (Remund et al., 2000), deriving the surface wind-induced patterns over Antarctica by measuring the azimuthal modulation of backscatter (Long et al., 2000).
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In winter when soil surface freezes, dielectric properties of the soil changes significantly which results in low backscatter values. As snow begins to fall and accumulates over the surface, due to volume scattering, backscatter signals increase depending on microwave frequency. The response of dry snow volume to microwaves is rather complex and depends on snow properties like snow depth, density, and average grain size as well as the age of snowpack. With increasing temperature in spring, snow begins to melt and water covers the surface of snow pack which causes a sudden drop in backscatter. After snow melting period, soil and vegetation begin to thaw and consequently backscatter arise again. Figure 8 shows a typical example of freeze/thaw process as described above observable in ASCAT normalized backscatter at 40 . High diurnal difference of backscatter (green bars) implies frozen condition in the morning and thawing in the evening which can be used as an indicator of the transition between different phases.
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Figure 8.
ASCAT normalized backscatter at 40 indicating seasonal freeze/thaw process.
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The high temporal sampling of the scatterometers in Polar Regions despite the frequent cloud cover and poor sunlight make them valuable instruments for sea ice observations. The sea ice imaging is based on the sensitivity of scatterometer to ice roughness and relatively high difference between the backscatter from open water and sea ice.
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\n\t\t\t\tLong et al. (1999) used a simple linear function to approximate the backscatter at 40 (reference incidence angle):
where A is the \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tσ\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t at 40 incidence and B describes the incidence angle dependency of backscatter.
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The A and B parameters are calculated after combining the scatterometer observations from multiple passes from several days and using the Scatterometer Image Reconstruction (SIR) algorithm to enhance the resolution (Early et al., 2001). The A and B images represent the backscatter properties of the surface and are related to ice and snow characteristics over the imaging period (Long et al., 2001). Figure 9 illustrates examples of the normalized backscatter retrieved from ERS-1/2 scatterometer data available through the Scatterometer Climate Record Pathfinder (SCP) project (NASA-SCP).
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7. Conclusion
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C-band scatterometers have demonstrated to be valuable sensors for large-scale observation of the Earth’s surface in a variety of disciplines. High temporal sampling in all weather conditions, multi-viewing capability and availability of long-term measurements make the European C-band scatterometers excellent Earth observation tools. Scatterometer data are used to extract geophysical parameters such as wind speed and direction, surface soil moisture, seasonal dynamics of vegetation, spatial and temporal variability of frozen train in high latitudes, snowmelt and sea ice. Furthermore the scatterometer data are utilized in hydrological modeling, observation of extreme events, flood and drought monitoring, and also used for climate change studies. The observations of the ERS-1/2 scatterometers
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Figure 9.
Images of parameter A in equation-8 (the normalized backscatter at 40 ) retrieved from ERS-2 scatterometer data after resolution enhancement. Adopted from (NSIDC).
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(SCATs) together with the new series of advanced scatterometers (ASCAT) onboard Metop satellites ensure long-term global observation (from 1991 until at least 2020).
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Acknowledgments
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This work was supported by the geoland-II project in frame of the Global Monitoring for the Environment and Security (GMES), a joint initiative of European Commission (EC) and European Space Agency (ESA), and the Austrian Research Promotion Agency (FFG) through the Global Monitoring of Soil Moisture (GMSM) project.
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\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/10393.pdf",chapterXML:"https://mts.intechopen.com/source/xml/10393.xml",downloadPdfUrl:"/chapter/pdf-download/10393",previewPdfUrl:"/chapter/pdf-preview/10393",totalDownloads:3347,totalViews:317,totalCrossrefCites:3,dateSubmitted:null,dateReviewed:null,datePrePublished:null,datePublished:"February 1st 2010",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/10393",risUrl:"/chapter/ris/10393",signatures:"Vahid Naeimi and Wolfgang Wagner",book:{id:"3717",type:"book",title:"Geoscience and Remote Sensing",subtitle:"New Achievements",fullTitle:"Geoscience and Remote Sensing New Achievements",slug:"geoscience-and-remote-sensing-new-achievements",publishedDate:"February 1st 2010",bookSignature:"Pasquale Imperatore and Daniele Riccio",coverURL:"https://cdn.intechopen.com/books/images_new/3717.jpg",licenceType:"CC BY-NC-SA 3.0",editedByType:"Edited by",isbn:null,printIsbn:"978-953-7619-97-8",pdfIsbn:"978-953-51-4566-0",isAvailableForWebshopOrdering:!0,editors:[{id:"4222",title:"Dr.",name:"Pasquale",middleName:null,surname:"Imperatore",slug:"pasquale-imperatore",fullName:"Pasquale Imperatore"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. C-band Scatterometers",level:"1"},{id:"sec_2_2",title:"2.1. SCAT onboard ERS satellites",level:"2"},{id:"sec_3_2",title:"2.2. ASCAT onboard Metop satellites",level:"2"},{id:"sec_5",title:"3. Wind Speed and Direction Measurement ",level:"1"},{id:"sec_6",title:"4. Monitoring Seasonal Dynamics of Vegetation",level:"1"},{id:"sec_7",title:"5. Soil Moisture Change Detection",level:"1"},{id:"sec_7_2",title:"5.1. TUWien change detection method",level:"2"},{id:"sec_8_2",title:"5.2. Surface soil moisture anomalies",level:"2"},{id:"sec_9_2",title:"5.3. Soil Water index (SWI)",level:"2"},{id:"sec_11",title:"6. Monitoring Cryosphere",level:"1"},{id:"sec_12",title:"7. 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Radar remote sensing and surface scattering and emission theory.\n\t\t\t'},{id:"B47",body:'\n\t\t\t\t\n\t\t\t\t\tUNESCO report\n\t\t\t\t\t2006 United Nations World Water Developement Report 2, Water, a Shared Responsibility, 121\n\t\t\t\t\n\t\t\t'},{id:"B48",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tVerhoef\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t and Ad Stoffelen 2009 Validation of ASCAT 12.5 -km winds, version 1.2, SAF/OSI/CDOP/KNMI/TEC/RP/147, EUMETSAT.\n\t\t\t'},{id:"B49",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWagner\n\t\t\t\t\t\t\tW.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1998 Soil Moisture Retrieval from ERS Scatterometer Data, dissertation, 111 Vienna University of Technology, Vienna.\n\t\t\t'},{id:"B50",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWagner\n\t\t\t\t\t\t\tW.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLemoine\n\t\t\t\t\t\t\tG.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBorgeaud\n\t\t\t\t\t\t\tM.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tRott\n\t\t\t\t\t\t\tH.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t1999a A study of vegetation cover effects on ERS scatterometer data, IEEE Transactions on Geoscience and Remote Sensing, 37\n\t\t\t\t\t938\n\t\t\t\t\t948 .\n\t\t\t'},{id:"B51",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWagner\n\t\t\t\t\t\t\tW.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLemoine\n\t\t\t\t\t\t\tG.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tRott\n\t\t\t\t\t\t\tH.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1999b\n\t\t\t\t\tA method for estimating soil moisture from ERS scatterometer and soil data, Remote Sensing of Environment, 70\n\t\t\t\t\t191\n\t\t\t\t\t207.\n\t\t\t'},{id:"B52",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWismann\n\t\t\t\t\t\t\tV.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2000\n\t\t\t\t\tMonitoring of seasonal snowmelt on Greenland with ERS scatterometer data, IEEE Transactions on Geoscience and Remote Sensing, 38\n\t\t\t\t\t1821\n\t\t\t\t\n\t\t\t'},{id:"B53",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWismann\n\t\t\t\t\t\t\tV.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBoehnke\n\t\t\t\t\t\t\tK.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1997 Monitoring snow properties on Greenland with ERS scatterometer and SAR, European Space Agency, (Special Publication) ESA SP. 857\n\t\t\t\t\t861 .\n\t\t\t'},{id:"B54",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWismann\n\t\t\t\t\t\t\tV. R.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBoehnke\n\t\t\t\t\t\t\tK.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSchmullius\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1994\n\t\t\t\t\tGlobal land surface monitoring using the ERS-1 scatterometer, International Geoscience and Remote Sensing Symposium (IGARSS), 1488\n\t\t\t\t\n\t\t\t'},{id:"B55",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWoodhouse\n\t\t\t\t\t\t\tI. H.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHoekman\n\t\t\t\t\t\t\tD. H.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2000\n\t\t\t\t\tDetermining land-surface parameters from the ERS wind scatterometer, IEEE Transactions on Geoscience and Remote Sensing, 38\n\t\t\t\t\t126\n\t\t\t\t\t140 .\n\t\t\t'},{id:"B56",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZine\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tJarlan\n\t\t\t\t\t\t\tL.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFrison\n\t\t\t\t\t\t\tP. L.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tMougin\n\t\t\t\t\t\t\tE.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHiernaux\n\t\t\t\t\t\t\tP.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tRudant\n\t\t\t\t\t\t\tJ. P.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2005\n\t\t\t\t\tLand surface parameter monitoring with ERS scatterometer data over the Sahel: A comparison between agro-pastoral and pastoral areas, Remote Sensing of Environment, 96\n\t\t\t\t\t438\n\t\t\t\t\n\t\t\t'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Vahid Naeimi",address:null,affiliation:'
'}],corrections:null},book:{id:"3717",type:"book",title:"Geoscience and Remote Sensing",subtitle:"New Achievements",fullTitle:"Geoscience and Remote Sensing New Achievements",slug:"geoscience-and-remote-sensing-new-achievements",publishedDate:"February 1st 2010",bookSignature:"Pasquale Imperatore and Daniele Riccio",coverURL:"https://cdn.intechopen.com/books/images_new/3717.jpg",licenceType:"CC BY-NC-SA 3.0",editedByType:"Edited by",isbn:null,printIsbn:"978-953-7619-97-8",pdfIsbn:"978-953-51-4566-0",isAvailableForWebshopOrdering:!0,editors:[{id:"4222",title:"Dr.",name:"Pasquale",middleName:null,surname:"Imperatore",slug:"pasquale-imperatore",fullName:"Pasquale Imperatore"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},profile:{item:{id:"356318",title:"Dr.",name:"Paz",middleName:null,surname:"Otero",email:"paz.otero@uvigo.es",fullName:"Paz Otero",slug:"paz-otero",position:null,biography:"Dr. Paz Otero received a PhD in Food Science at the University of Santiago de Compostela (USC), Spain in 2013. After that, she has held postdoctoral research positions in Limerick Institute of Technology, Ireland (2014-2017) and The Institute of Food Science Research, CIAL (2017-2018) at the Autonomous University of Madrid. Currently, she is a researcher in the Department of Analytical and Food Chemistry from the University of Vigo, Spain. She has published extensively in the field of food chemistry, toxicology, analytical chemistry, pharmacology, nutrition and phycotoxin biology with more than 50 authored research articles, 60 contributions to international congress and 8 chapters books to date. Dr. Paz Otero also serves as an invited reviewer for several research journals, editorial board member for online free-access journals and guest editor for special issues.",institutionString:"University of Vigo",profilePictureURL:"https://mts.intechopen.com/storage/users/356318/images/system/356318.jpg",totalCites:0,totalChapterViews:"0",outsideEditionCount:0,totalAuthoredChapters:"0",totalEditedBooks:"0",personalWebsiteURL:null,twitterURL:null,linkedinURL:null,institution:{name:"University of Vigo",institutionURL:null,country:{name:"Spain"}}},booksEdited:[],chaptersAuthored:[],collaborators:[]},generic:{page:{slug:"copyright-policy",title:"Copyright Policy",intro:"
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Simulation results show a comparison between the performances of each of the proposed techniques depending on the nonlinear model of the quadcopter system under investigation; the trajectory tracking has been achieved properly for different types of trajectories, i.e., spiral trajectory, in the presence of unknown disturbances. Moreover, the practical results coincided with the results of the simulation results.",book:{id:"7792",slug:"unmanned-robotic-systems-and-applications",title:"Unmanned Robotic Systems and Applications",fullTitle:"Unmanned Robotic Systems and Applications"},signatures:"Abdulkader Joukhadar, Mohammad Alchehabi and Adnan Jejeh",authors:null}],onlineFirstChaptersFilter:{topicId:"22",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81719",title:"Service Robots in Healthcare Settings",slug:"service-robots-in-healthcare-settings",totalDownloads:5,totalDimensionsCites:0,doi:"10.5772/intechopen.104640",abstract:"Robots will play a part in all aspects of healthcare. 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As for regenerative braking, the torque control mode of operation is shown to be suitable for harvesting energy and both techniques showed similar performance levels. 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The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null,scope:"
\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
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\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
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\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
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He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"351159",title:"BSc.",name:"Kalum J.",middleName:null,surname:"Ost",slug:"kalum-j.-ost",fullName:"Kalum J. Ost",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"325029",title:"Dr.",name:"Prem Chand",middleName:null,surname:"Jain",slug:"prem-chand-jain",fullName:"Prem Chand Jain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Shiv Nadar University",country:{name:"India"}}},{id:"357275",title:"Dr.",name:"Thomas",middleName:null,surname:"Mih",slug:"thomas-mih",fullName:"Thomas Mih",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Buea",country:{name:"Cameroon"}}},{id:"305305",title:"Dr.",name:"Arturo Yosimar",middleName:null,surname:"Jaen-Cuellar",slug:"arturo-yosimar-jaen-cuellar",fullName:"Arturo Yosimar Jaen-Cuellar",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"305315",title:"Dr.",name:"David Alejandro",middleName:null,surname:"Elvira-Ortiz",slug:"david-alejandro-elvira-ortiz",fullName:"David Alejandro Elvira-Ortiz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"344374",title:"Dr.",name:"Manuel",middleName:null,surname:"Toledano-Ayala",slug:"manuel-toledano-ayala",fullName:"Manuel Toledano-Ayala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}}]}},subseries:{item:{id:"40",type:"subseries",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"
\r\n\tIn general, the harsher the environmental conditions in an ecosystem, the lower the biodiversity. Changes in the environment caused by human activity accelerate the impoverishment of biodiversity.
\r\n
\r\n\tBiodiversity refers to “the variability of living organisms from any source, including terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; it includes diversity within each species, between species, and that of ecosystems”.
\r\n
\r\n\tBiodiversity provides food security and constitutes a gene pool for biotechnology, especially in the field of agriculture and medicine, and promotes the development of ecotourism.
\r\n
\r\n\tCurrently, biologists admit that we are witnessing the first phases of the seventh mass extinction caused by human intervention. It is estimated that the current rate of extinction is between a hundred and a thousand times faster than it was when man first appeared. The disappearance of species is caused not only by an accelerated rate of extinction, but also by a decrease in the rate of emergence of new species as human activities degrade the natural environment. The conservation of biological diversity is "a common concern of humanity" and an integral part of the development process. Its objectives are “the conservation of biological diversity, the sustainable use of its components, and the fair and equitable sharing of the benefits resulting from the use of genetic resources”.
\r\n
\r\n\tThe following are the main causes of biodiversity loss:
\r\n
\r\n\t• The destruction of natural habitats to expand urban and agricultural areas and to obtain timber, minerals and other natural resources.
\r\n
\r\n\t• The introduction of alien species into a habitat, whether intentionally or unintentionally which has an impact on the fauna and flora of the area, and as a result, they are reduced or become extinct.
\r\n
\r\n\t• Pollution from industrial and agricultural products, which devastate the fauna and flora, especially those in fresh water.
\r\n
\r\n\t• Global warming, which is seen as a threat to biological diversity, and will become increasingly important in the future.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/40.jpg",hasOnlineFirst:!1,hasPublishedBooks:!1,annualVolume:11968,editor:{id:"209149",title:"Prof.",name:"Salustiano",middleName:null,surname:"Mato",slug:"salustiano-mato",fullName:"Salustiano Mato",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLREQA4/Profile_Picture_2022-03-31T10:23:50.png",biography:"Salustiano Mato de la Iglesia (Santiago de Compostela, 1960) is a doctor in biology from the University of Santiago and a Professor of zoology at the Department of Ecology and Animal Biology at the University of Vigo. He has developed his research activity in the fields of fauna and soil ecology, and in the treatment of organic waste, having been the founder and principal investigator of the Environmental Biotechnology Group of the University of Vigo.\r\nHis research activity in the field of Environmental Biotechnology has been focused on the development of novel organic waste treatment systems through composting. 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A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. 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The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. 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The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. 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Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",annualVolume:11403,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:null,institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda",middleName:"R.",surname:"Gharieb",fullName:"Reda Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. 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We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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